检索结果-内蒙古大学图书馆

Corrigendum to "Patterns of co-occurring birth defects among infants with hypospadiasˮ [J Pediatr Urol 17 (2021) 64.e1-64.e8]

引用

Journal of pediatric urology 2021年第4期17卷 e1页

作者： Katherine L Ludorf Renata H Benjamin Maria Luisa Navarro Sanchez Scott D McLean Hope Northrup Laura E Mitchell Peter H Langlois Mark A Canfield Angela E Scheuerle Daryl A Scott Christian P Schaaf Joseph W Ray Omobola Oluwafemi Han Chen Michael D Swartz Philip J Lupo A J Agopian Department of Epidemiology Human Genetics and Environmental Sciences UTHealth School of Public Health Houston TX USA. Clinical Genetics Section The Children's Hospital of San Antonio San Antonio TX USA. Department of Pediatrics Division of Medical Genetics McGovern Medical School University of Texas Health Science Center at Houston Houston TX USA. Birth Defects Epidemiology and Surveillance Branch Texas Department of State Health Services Austin TX USA. Department of Pediatrics Division of Genetics and Metabolism University of Texas Southwestern Medical Center Dallas TX USA. Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Department of Molecular Physiology and Biophysics Baylor College of Medicine Houston TX USA. Jan and Dan Duncan Neurological Research Institute Texas Children's Hospital Houston TX USA Heidelberg University Institute of Human Genetics Heidelberg Germany. Department of Pediatrics Division of Medical Genetics and Metabolism University of Texas Medical Branch Galveston TX USA. Department of Epidemiology Human Genetics and Environmental Sciences UTHealth School of Public Health Houston TX USA Center for Precision Health UTHealth School of Public Health and UTHealth School of Biomedical Informatics Houston TX USA. Department of Biostatistics and Data Science UTHealth School of Public Health Houston TX USA. Department of Pediatrics Section of Hematology-Oncology Baylor College of Medicine Houston TX USA. Department of Epidemiology Human Genetics and Environmental Sciences UTHealth School of Public Health Houston TX USA. Electronic address: a.j.agopian@uth.tmc.edu.

来源：评论

学校读者我要写书评

暂无评论

A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease (Sep, 10.1038/s41588-021-00921-z, 2021)

引用

NATURE GENETICS 2022年第7期54卷 1062-1062页

作者： Wightman, Douglas P. Jansen, Iris E. Savage, Jeanne E. Shadrin, Alexey A. Bahrami, Shahram Holland, Dominic Rongve, Arvid Borte, Sigrid Winsvold, Bendik S. Drange, Ole Kristian Martinsen, Amy E. Skogholt, Anne Heidi Willer, Cristen Brathen, Geir Bosnes, Ingunn Nielsen, Jonas Bille Fritsche, Lars G. Thomas, Laurent F. Pedersen, Linda M. Gabrielsen, Maiken E. Johnsen, Marianne Bakke Meisingset, Tore Wergeland Zhou, Wei Proitsi, Petroula Hodges, Angela Dobson, Richard Velayudhan, Latha Heilbron, Karl Auton, Adam Sealock, Julia M. Davis, Lea K. Pedersen, Nancy L. Reynolds, Chandra A. Karlsson, Ida K. Magnusson, Sigurdur Stefansson, Hreinn Thordardottir, Steinunn Jonsson, Palmi V. Snaedal, Jon Zettergren, Anna Skoog, Ingmar Kern, Silke Waern, Margda Zetterberg, Henrik Blennow, Kaj Stordal, Eystein Hveem, Kristian Zwart, John-Anker Athanasiu, Lavinia Selnes, Per Saltvedt, Ingvild Sando, Sigrid B. Ulstein, Ingun Djurovic, Srdjan Fladby, Tormod Aarsland, Dag Selbaek, Geir Ripke, Stephan Stefansson, Kari Andreassen, Ole A. Posthuma, Danielle Department of Complex Trait Genetics Center for Neurogenomics and Cognitive Research Amsterdam Neuroscience VU Amsterdam Amsterdam the Netherlands Department of Child and Adolescent Psychiatry and Pediatric Psychology Section Complex Trait Genetics Amsterdam Neuroscience Vrije Universiteit Medical Center Amsterdam University Medical Center Amsterdam the Netherlands NORMENT Centre University of Oslo Oslo Norway Institute of Clinical Medicine University of Oslo Oslo Norway Division of Mental Health and Addiction Oslo University Hospital Oslo Norway Research and Communication Unit for Musculoskeletal Health (FORMI) Department of Research Innovation and Education Division of Clinical Neuroscience Oslo University Hospital Oslo Norway K. G. Jebsen Center for Genetic Epidemiology Department of Public Health and Nursing Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway Department of Research Innovation and Education Division of Clinical Neuroscience Oslo University Hospital Oslo Norway Department of Neurology Akershus University Hospital Lørenskog Norway Department of Geriatric Medicine Oslo University Hospital Oslo Norway Norwegian National Advisory Unit on Ageing and Health Vestfold Hospital Trust Tønsberg Norway Department of Neurosciences University of California San Diego La Jolla CA USA Department of Research and Innovation Helse Fonna Haugesund Hospital Haugesund Norway The University of Bergen Institute of Clinical Medicine (K1) Bergen Norway Department of Neurology Oslo University Hospital Oslo Norway Department of Clinical and Molecular Medicine Norwegian University of Science and Technology Trondheim Norway Department of Internal Medicine Division of Cardiovascular Medicine University of Michigan Ann Arbor MI USA Department of Epidemiology Research Statens Serum Institut Copenhagen Denmark HUNT Research Center Department of Public Health and Nursing Faculty of Medicine and Health Scien

来源：评论

学校读者我要写书评

暂无评论

159 Dermoscopy versus videocapillaroscopy in the assessment of nailfold capillaroscopy images in patients with systemic sclerosis and healthy controls

引用

Rheumatology 2018年第SUPPL_3期57卷

作者： Dinsdale, Graham Peytrignet, Sebastien Moore, Tonia Berks, Michael Roberts, Christopher Manning, Joanne Allen, John Anderson, Marina Cutolo, Maurizio Hesselstrand, Roger Howell, Kevin Pizzorni, Carmen Smith, Vanessa Sulli, Alberto Wildt, Marie Taylor, Christopher Murray, Andrea Herrick, Ariane Centre for Musculoskeletal Research University of Manchester Salford Royal Hospital NHS Foundation Trust MAHSC Manchester UNITED KINGDOM Centre for Imaging Sciences Division of Informatics Imaging & Data Sciences University of Manchester Manchester UNITED KINGDOM Centre for Biostatistics Division of Population Health Health Services Research & Primary Care University of Manchester Manchester UNITED KINGDOM Microvascular Diagnostics Northern Medical Physics and Clinical Engineering Freeman Hospital Newcastle-upon-Tyne UNITED KINGDOM Institute of Ageing and Chronic Disease University of Liverpool Liverpool UNITED KINGDOM Research Laboratory and Academic Division of Clinical Rheumatology Department of Internal Medicine University of Genova Genova ITALY Department of Clinical Sciences Section of Rheumatology Lund University Lund SWEDEN Institute of Immunity and Transplantation University College London Royal Free Campus London UNITED KINGDOM Research Laboratory and Academic Division of Clinical Rheumatology Dept. Internal Medicine University of Genova Genova ITALY Department of Rheumatology Ghent University Hospital Faculty of Internal Medicine Ghent University Ghent BELGIUM Research Laboratory and Academic Division of Clinical Rheumatology Dept. Internal Medicine University of Genova Manchester ITALY NIHR Manchester Musculoskeletal Biomedical Research Centre Central Manchester NHS Foundation Trust Manchester Academic Health Science Centre Manchester UNITED KINGDOM

来源：评论

学校读者我要写书评

暂无评论

Author Correction: A multi-ancestry genetic study of pain intensity in 598,339 veterans

引用

Nature medicine 2024年第7期30卷 2088页

作者： Sylvanus Toikumo Rachel Vickers-Smith Zeal Jinwala Heng Xu Divya Saini Emily E Hartwell Mirko Pavicic Kyle A Sullivan Ke Xu Daniel A Jacobson Joel Gelernter Christopher T Rentsch Eli Stahl Martin Cheatle Hang Zhou Stephen G Waxman Amy C Justice Rachel L Kember Henry R Kranzler Mental Illness Research Education and Clinical Center Crescenz VAMC Philadelphia PA USA. Department of Psychiatry University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Epidemiology and Environmental Health University of Kentucky College of Public Health Lexington KY USA. Biosciences Division Oak Ridge National Laboratory Oak Ridge TN USA. Veterans Affairs Connecticut Healthcare System West Haven CT USA. Department of Psychiatry Yale University School of Medicine New Haven CT USA. Department of Medicine Yale University School of Medicine New Haven CT USA. London School of Hygiene & Tropical Medicine London UK. Regeneron Genetics Center Tarrytown NY USA. Section of Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT USA. Department of Neurology Yale University School of Medicine New Haven CT USA. Yale University School of Public Health New Haven CT USA. Mental Illness Research Education and Clinical Center Crescenz VAMC Philadelphia PA USA. kranzler@pennmedicine.upenn.edu. Department of Psychiatry University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. kranzler@pennmedicine.upenn.edu.

来源：评论

学校读者我要写书评

暂无评论

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

arXiv

引用

arXiv 2023年

作者： Moawad, Ahmed W. Janas, Anastasia Baid, Ujjwal Ramakrishnan, Divya Saluja, Rachit Ashraf, Nader Jekel, Leon Amiruddin, Raisa Adewole, Maruf Albrecht, Jake Anazodo, Udunna Aneja, Sanjay Anwar, Syed Muhammad Bergquist, Timothy Calabrese, Evan Chiang, Veronica Chung, Verena Conte, Gian Marco Marco Dako, Farouk Eddy, James Ezhov, Ivan Familiar, Ariana Farahani, Keyvan Iglesias, Juan Eugenio Jiang, Zhifan Johanson, Elaine Kazerooni, Anahita Fathi Kofler, Florian Krantchev, Kiril LaBella, Dominic Van Leemput, Koen Li, Hongwei Bran Linguraru, Marius George Link, Katherine E. Liu, Xinyang Maleki, Nazanin Meier, Zeke Menze, Bjoern H. Moy, Harrison Osenberg, Klara Piraud, Marie Reitman, Zachary Shinohara, Russel Takeshi Tahon, Nourel hoda Nada, Ayman Velichko, Yuri S. Wang, Chunhao Wiestler, Benedikt Wiggins, Walter Shafique, Umber Willms, Klara Avesta, Arman Bousabarah, Khaled Chakrabarty, Satrajit Gennaro, Nicolo Holler, Wolfgang Kaur, Manpreet LaMontagne, Pamela Lin, MingDe Lost, Jan Marcus, Daniel S. Maresca, Ryan Merkaj, Sarah Nada, Ayaman Pedersen, Gabriel Cassinelli von Reppert, Marc Sotiras, Aristeidis Teytelboym, Oleg Tillmans, Niklas Westerhoff, Malte Youssef, Ayda Godfrey, Devon Floyd, Scott Rauschecker, Andreas Villanueva-Meyer, Javier Pflüger, Irada Cho, Jaeyoung Bendszus, Martin Brugnara, Gianluca Cramer, Justin Perez-Carillo, Gloria Guzman J. Johnson, Derek R. Kam, Anthony Kwan, Benjamin Yin Ming Lai, Lillian Lall, Neil U. Memon, Fatima Patro, Satya Narayana Petrovic, Bojan So, Tiffany Y. Thompson, Gerard Wu, Lei Schrickel, E. Brooke Bansal, Anu Barkhof, Frederik Besada, Cristina Chu, Sammy Druzgal, Jason Dusoi, Alexandru Farage, Luciano Feltrin, Fabricio Fong, Amy Fung, Steve H. Gray, R. Ian Ikuta, Ichiro Iv, Michael Postma, Alida A. Mahajan, Amit Joyner, David Krumpelman, Chase Letourneau-Guillon, Laurent Lincoln, Christie M. Maros, Mate E. Miller, Elka Morón, Fanny Nimchinsky, Esther A. Ozsarlak, Ozkan Patel, Uresh Rohatgi, Saurabh Saha, Atin Sayah, Anousheh Schwartz, Eric D. Shih, Robert Shiroishi, Mark Trinity health Mid Atlantic Hosiptals DarbyPA United States Department of Radiology and Biomedical Imaging Yale School of Medicine New HavenCT United States Division of Computational Pathology Department of Pathology and Laboratory Medicine School of Medicine Indiana University IndianapolisIN United States Department of Electical and Computer Engineering Cornell University Cornell Tech New YorkNY United States Department of Radiology Weill Cornell Medicine New YorkNY United States ImagineQuant Children’s Hospital of Philadelphia PhiladelphiaPA United States College of Medicine Alfaisal University Riyadh Saudi Arabia DKFZ Division of Translational Neurooncology The WTZ German Cancer Consortium DKTK Partner Site University Hospital Essen Essen Germany Medical Artificial Intelligence Lab Crestview Radiology Lagos Nigeria Sage Bionetworks SeattleWA United States Montreal Neurological Institute McGill University Montreal Canada lab Crestview Radiology Lagos Nigeria Department of Therapeutic Radiology Yale School of Medicine New HavenCT United States Sheikh Zayed Institute for Pediatric Surgical Innovation Children’s National Hospital WashingtonDC United States Department of Radiology Mayo Clinic RochesterMN United States Department of Radiology Duke University Medical Center DurhamNC United States Department of Neurosurgery Yale School of Medicine New HavenCT United States Center for Global Health Perelman School of Medicine University of Pennsylvania PA United States Department of Informatics Technical University Munich Germany Children’s Hospital of Philadelphia University of Pennsylvania PhiladelphiaPA United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD United States Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Children’s National Hospital WashingtonDC United States PrecisionFDA U.S. Food and Drug Administration S

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well-annotated, diverse d

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Diabetic foot ulcers segmentation challenge report: Benchmark and analysis

引用

Medical image analysis 2024年 94卷 103153页

作者： Moi Hoon Yap Bill Cassidy Michal Byra Ting-Yu Liao Huahui Yi Adrian Galdran Yung-Han Chen Raphael Brüngel Sven Koitka Christoph M Friedrich Yu-Wen Lo Ching-Hui Yang Kang Li Qicheng Lao Miguel A González Ballester Gustavo Carneiro Yi-Jen Ju Juinn-Dar Huang Joseph M Pappachan Neil D Reeves Vishnu Chandrabalan Darren Dancey Connah Kendrick Department of Computing and Mathematics Manchester Metropolitan University John Dalton Building Chester Street Manchester M1 5GD United Kingdom Lancashire Teaching Hospitals NHS Trust Preston PR2 9HT United Kingdom. Electronic address: m.yap@mmu.ac.uk. Department of Computing and Mathematics Manchester Metropolitan University John Dalton Building Chester Street Manchester M1 5GD United Kingdom. Institute of Fundamental Technological Research Polish Academy of Sciences Warsaw Poland RIKEN Center for Brain Science Wako Japan. Department of Computer Science National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu Taiwan. West China Biomedical Big Data Center West China Hospital Sichuan University Chengdu China. BCN Medtech Universitat Pompeu Fabra Barcelona Spain AIML University of Adelaide Australia. Institute of Electronics National Yang Ming Chiao Tung University No. 1001 University Road Hsinchu 300 Taiwan. Department of Computer Science University of Applied Sciences and Arts Dortmund (FH Dortmund) Emil-Figge-Str. 42 44227 Dortmund Germany Institute for Medical Informatics Biometry and Epidemiology (IMIBE) University Hospital Essen Zweigertstr. 37 45130 Essen Germany Institute for Artificial Intelligence in Medicine (IKIM) University Hospital Essen Girardetstr. 2 45131 Essen Germany. Institute for Artificial Intelligence in Medicine (IKIM) University Hospital Essen Girardetstr. 2 45131 Essen Germany Institute of Diagnostic and Interventional Radiology and Neuroradiology University Hospital Essen Hufelandstr. 55 45147 Essen Germany. Institute for Medical Informatics Biometry and Epidemiology (IMIBE) University Hospital Essen Zweigertstr. 37 45130 Essen Germany. West China Biomedical Big Data Center West China Hospital Sichuan University Chengdu China Shanghai Artificial Intelligence Laboratory Shanghai China. School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China BCN Medtech Universit

Monitoring the healing progress of diabetic foot ulcers is a challenging process. Accurate segmentation of foot ulcers can help podiatrists to quantitatively measure the size of wound regions to assist prediction of healing status. The main challenge in this field is the lack of publicly available manual delineation, which can be time consuming and laborious. Recently, methods based on deep learning have shown excellent results in automatic segmentation of medical images, however, they require large-scale datasets for training, and there is limited consensus on which methods perform the best. The 2022 Diabetic Foot Ulcers segmentation challenge was held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention, which sought to address these issues and stimulate progress in this research domain. A training set of 2000 images exhibiting diabetic foot ulcers was released with corresponding segmentation ground truth masks. Of the 72 (approved) requests from 47 countries, 26 teams used this data to develop fully automated systems to predict the true segmentation masks on a test set of 2000 images, with the corresponding ground truth segmentation masks kept private. Predictions from participating teams were scored and ranked according to their average Dice similarity coefficient of the ground truth masks and prediction masks. The winning team achieved a Dice of 0.7287 for diabetic foot ulcer segmentation. This challenge has now entered a live leaderboard stage where it serves as a challenging benchmark for diabetic foot ulcer segmentation.

关键词： Convolutional neural networks Deep learning Diabetic foot ulcers Metrics Segmentation

来源：评论

学校读者我要写书评

暂无评论

Allogeneic Hematopoietic Cell Transplantation (HCT) Vs. Non-HCT Consolidation Therapies in Acute Myeloid Leukemia (AML) Patients 60-75 Years of Age in First Complete Remission (CR1): An Alliance (A151509), SWOG, ECOG-ACRIN and CIBMTR Study

引用

Blood 2018年 132卷 2170-2170页

作者： Celalettin Ustun Jennifer Le-Rademacher Hai-Lin Wang Megan Othus Zhuoxin Sun Brittny Major Mei-Jie Zhang Elizabeth Storrick Jacqueline M Lafky Selina Chow Krzysztof Mrózek Eyal C. Attar Clara D. Bloomfield Larry D Cripe Richard A. Larson Guido Marcucci Gail J. Roboz Geoffrey L. Uy Richard M. Stone Aminah Jatoi Andrew S Artz Blood and Marrow Transplant Program University of Minnesota Minneapolis MN Dept of Biomedical Statistics and Informatics Mayo Clinic Rochester MN CIBMTR (Center for International Blood and Marrow Transplant Research) Department of Medicine Medical College of Wisconsin Milwaukee WI Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle Harvard T.H. Chan School of Public Health Boston Department of Health Sciences Research Mayo Clinic Rochester Alliance Statistics and Data Center Mayo Clinic Rochester MN Mayo Clinic Rochester University of Chicago Comprehensive Cancer Center Chicago The Ohio State University Comprehensive Cancer Center Columbus OH Massachusetts General Hospital Boston Agios Pharmaceuticals Inc. Cambridge MA Comprehensive Cancer Center The Ohio State University Columbus OH Indiana University Simon Cancer Center Indianapolis Department of Medicine and Comprehensive Cancer Center University of Chicago Chicago IL Department of Hematological Malignancies Translational Science Gehr Family Center for Leukemia Research Hematologic Malignancies and Stem Cell Transplantation Institute Beckman Research Institute City of Hope Medical Center Duarte CA Weill Cornell Medicine and The Weill Medical College of Cornell University New York NY Washington University School of Medicine Saint Louis MO Dana-Farber Cancer Institute Boston MA Department of Medicine Section of Hematology/Oncology University of Chicago Chicago IL

Introduction: The preferred post-remission therapy for older patients (pts) with AML remains uncertain. We compared outcomes for older AML pts in CR1 receiving HCT reported to the CIBMTR to older AML pts achieving CR1 on National Clinical Trials Network induction and non-HCT consolidation therapy (CT) trials. Methods: This study focused on pts 60-75 years of age treated between 2004 to 2013. CT pts (n=211) underwent induction and consolidation on Alliance for Clinical Trials in Oncology, ECOG-ACRIN or SWOG clinical trials for initial therapy for newly diagnosed AML; the CIBMTR provided data for HCT pts (n=431). CT patients received at least one cycle of CT on study and were excluded if HCT occurred at any time. Time to event started at CR1 and pts entered at CT or HCT, respectively, using left-truncation to account for differential entry times. Results: For the CT cohort, first consolidation included standard therapy (e.g., cytarabine or a hypomethylating agent) and additional study drug (e.g., bortezomib, dasatinib, sorafenib, and Zosuquidar, gemtuzumab) or tipifarnib alone. Among HCT pts, the donor was a HLA-matched sibling or unrelated donor (URD) in 66% and the others were partially HLA-matched/mismatched URD (10%) or cord blood (24%). HCT pts were younger and more frequently had high-risk AML (high WBC, secondary AML and unfavorable cytogenetics) (Table). The median time from CR1 to HCT and CT was 3.2 and 0.5 months, respectively. Allogeneic HCT showed worse overall survival (OS) (HR=1.52, p=0.02) prior to 9 months and better OS thereafter (HR= 0.53, p <0.0001) relative to CT (figure 1A). Treatment-related mortality (TRM) was worse after HCT in the first 9 months (HR=2.8, CI: 1.5 -5.2, p =.0009), while relapse was less frequent beyond 9 months after treatment (HR = 0.42, CI: 0.29 to 0.61, p <.0001). Despite higher early TRM, HCT recipients went on to manifest superior OS [5 year OS: HCT 29% (24-34%), CT 13.8% (9 -22%)] (Figure 1A). The benefit of HCT for surviv

关键词：

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation

arXiv

引用

arXiv 2024年

作者： LaBella, Dominic Schumacher, Katherine Mix, Michael Leu, Kevin McBurney-Lin, Shan Nedelec, Pierre Villanueva-Meyer, Javier Shapey, Jonathan Vercauteren, Tom Chia, Kazumi Ivory, Marina Barfoot, Theodore Al-Salihi, Omar Leu, Justin Halasz, Lia Velichko, Yury Wang, Chunhao Kirkpatrick, John Floyd, Scott Reitman, Zachary J. Mullikin, Trey Bagci, Ulas Sachdev, Sean Hattangadi-Gluth, Jona A. Seibert, Tyler M. Farid, Nikdokht Puett, Connor Pease, Matthew W. Shiue, Kevin Anwar, Syed Muhammad Faghani, Shahriar Taylor, Peter Haider, Muhammad Ammar Warman, Pranav Albrecht, Jake Jakab, András Moassefi, Mana Chung, Verena Aristizabal, Alejandro Karargyris, Alexandros Kassem, Hasan Pati, Sarthak Sheller, Micah Coley, Aaron Huang, Christina Ghanta, Siddharth Schneider, Alex Sharp, Conrad Saluja, Rachit Kofler, Florian Lohmann, Philipp Vollmuth, Phillipp Gagnon, Louis Adewole, Maruf Li, Hongwei Bran Kazerooni, Anahita Fathi Tahon, Nourel Hoda Anazodo, Udunna Moawad, Ahmed W. Menze, Bjoern Linguraru, Marius George Aboian, Mariam Wiestler, Benedikt Baid, Ujjwal Conte, Gian-Marco Rauschecker, Andreas M. Nada, Ayman Abayazeed, Aly H. Huang, Raymond de Verdier, Maria Correia Rudie, Jeffrey D. Bakas, Spyridon Calabrese, Evan Department of Radiation Oncology Duke University Medical Center DurhamNC United States Department of Radiation Oncology SUNY Upstate Medical University SyracuseNY United States San FranciscoCA United States Department of Neurosurgery King’s College Hospital London United Kingdom School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom Guy’s and St Thomas’ NHS Foundation Trust United Kingdom Department of Radiation Oncology University of Washington SeattleWA United States Department of Radiology Northwestern University EvanstonIL United States Department of Radiation Oncology Northwestern University EvanstonIL United States Department of Radiation Medicine and Applied Sciences University of California San Diego La Jolla CA United States Department of Radiology University of California San Diego La Jolla CA United States Department of Bioengineering University of California San Diego La Jolla CA United States Department of Neurological Surgery Indiana University School of Medicine IndianapolisIN United States Department of Radiation Oncology Indiana University IndianapolisIN United States Children’s National Hospital WashingtonDC United States George Washington University WashingtonDC United States Mayo Clinic RochesterMN United States CMH Lahore Medical College Lahore Pakistan Duke University Medical Center School of Medicine DurhamNC United States Sage Bionetworks United States University of Zürich Zürich Switzerland Artificial Intelligence Lab Department of Radiology Mayo Clinic RochesterMN United States MLCommons United States Factored AI United States Center For Federated Learning in Medicine Indiana University IndianapolisIN United States Division of Computational Pathology Department of Pathology and Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Medical Working Group MLCommons San FranciscoCA United States Intel United States Duke Universi

The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aims to advance automated segmentation algorithms using the largest known multi-institutional dataset of 750 radiotherapy planning brain MRIs with expert-annotated target labels for patients with intact or postoperative meningioma that underwent either conventional external beam radiotherapy or stereotactic radiosurgery. Each case includes a defaced 3D post-contrast T1-weighted radiotherapy planning MRI in its native acquisition space, accompanied by a single-label "target volume" representing the gross tumor volume (GTV) and any at-risk postoperative site. Target volume annotations adhere to established radiotherapy planning protocols, ensuring consistency across cases and institutions. For preoperative meningiomas, the target volume encompasses the entire GTV and associated nodular dural tail, while for postoperative cases, it includes at-risk resection cavity margins as determined by the treating institution. Case annotations were reviewed and approved by expert neuroradiologists and radiation oncologists. Participating teams will develop, containerize, and evaluate automated segmentation models using this comprehensive dataset. Model performance will be assessed using an adapted lesion-wise Dice Similarity Coefficient and the 95% Hausdorff distance. The top-performing teams will be recognized at the Medical Image Computing and Computer Assisted Intervention Conference in October 2024. BraTS-MEN-RT is expected to significantly advance automated radiotherapy planning by enabling precise tumor segmentation and facilitating tailored treatment, ultimately improving patient outcomes. © 2024, CC BY.

关键词： Radiotherapy

来源：评论

学校读者我要写书评

暂无评论

The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

引用

NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

来源：评论

学校读者我要写书评

暂无评论

Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

引用

NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：