检索结果-内蒙古大学图书馆

Accuracy of computer-assisted image analysis in the diagnosis of maxillofacial radiolucent lesions: A systematic review and meta-analysis

引用

DENTOMAXILLOFACIAL RADIOLOGY 2020年第3期49卷 20190204页

作者： Silva, Virginia K. S. Vieira, Walbert A. Bernardino, Italo M. Travencolo, Bruno A. N. Bittencourt, Marcos A., V Blumenberg, Cauane Paranhos, Luiz R. Galvao, Hebel C. Univ Fed Rio Grande do Norte Postgrad Program Hlth Sci Dept Dent Natal RN Brazil Univ Estadual Campinas Piracicaba Dent Sch Endodont Div Postgrad Program Dent Piracicaba SP Brazil State Univ Paraiba Postgrad Program Dent Dept Dent Campina Grande Paraiba Brazil Univ Fed Uberlandia Sch Comp Ctr Exact Sci & Technol Uberlandia MG Brazil Univ Fed Bahia Sch Dent Dept Pediat & Community Dent Salvador BA Brazil Univ Fed Pelotas Postgrad Program Epidemiol Dept Social Med Pelotas RS Brazil Fed Univ Uberldndia Sch Dent Dept Prevent & Community Dent Uberlandia MG Brazil Univ Fed Rio Grande do Norte Dept Dent Natal RN Brazil

Objectives: This study aimed to search for scientific evidence concerning the accuracy of computer-assisted analysis for diagnosing maxillofacial radiolucent lesions. Methods: A systematic review was conducted according to the statements of Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols and considering 10 databases, including the gray literature. Protocol was registered at the International Prospective Register of Systematic Reviews (CRD42018089945). The population, intervention, comparison and outcome strategy was used to define the eligibility criteria and only diagnostic test studies were included. Their risk of bias was assessed by the Joanna Briggs Institute Critical Appraisal tool. Random-effects model meta-analysis was performed and heterogeneity among the included studies was estimated using the I-2 statistic. The grade of recommendation, assessment, development, and evaluation (GRADE) tool assessed the quality of evidence and strength of recommendation across included studies. Results: Out of 715 identified citations, four papers, published between 2009 and 2017, fulfilled the criteria and were included in this systematic review. A total of 191 lesions, classified as periapical granuloma and cyst, dentigerous cyst or keratocystic odontogenic tumor, were analyzed. All selected articles scored low risk of bias. The pooled accuracy estimation, regardless of the classification method used, was 88.75% (95% CI = 85.19-92.30). Heterogeneity test reached moderate values (I-2 = 57.89%). According to the GRADE tool, the analyzed outcome was classified as having low level of certainty. Conclusions: The overall evaluation showed all studies presented high accuracy rates of computer-aided diagnosis systems in classifying radiolucent maxillofacial lesions compared to histopathological biopsy. However, due to the moderate heterogeneity found among the studies included in this meta-analysis, a pragmatic recommendation about the use of computer

关键词： computer-assisted diagnosis computer-assisted image analysis computer-assisted image processing periapical cyst Maxillofacial pathology

来源：评论

学校读者我要写书评

暂无评论

image quality of virtual monochromatic and material density iodine images for evaluation of head and neck neoplasms using deep learning-based CT image reconstruction - A retrospective observational study

引用

EUROPEAN JOURNAL OF RADIOLOGY 2024年 181卷 111806-111806页

作者： Buerckenmeyer, Florian Graeger, Stephanie Mlynska, Lucja Guettler, Felix Ingwersen, Maja Teichgraeber, Ulf Kraemer, Martin Friedrich Schiller Univ Jena Jena Univ Hosp Dept Diagnost & Intervent Radiol Am Klinikum 1 D-07747 Jena Germany

Purpose: To compare the quality of deep learning image reconstructed (DLIR) virtual monochromatic images (VMI) and material density (MD) iodine images from dual-energy computed tomography (DECT) for the evaluation of head and neck neoplasms with CT scans from a conventional single-energy protocol. Method: A total of 294 head and neck CT scans (98 VMIs operated at 60 keV, 102 MD iodine images, and 94 images from a 120 kVp single-energy CT (SECT) protocol) were retrospectively evaluated. VMIs and MD iodine images were generated using the Gemstone Spectral Imaging (GSI) mode using DLIR and metal artifact reduction (MAR) algorithms. SECT images were generated using adaptive statistical iterative reconstruction (ASIR-V). images were scored by two independent readers on a 6-point Likert-type scale for overall image quality, vessel contrast, soft tissue contrast, noise texture, noise intensity, artifact reduction, and sharpness. Results: Subjective overall image quality was rated as superior or excellent in 98 % of DLIR-based MD iodine images and VMIs, but only in 55 % of ASIR-V-based SECT images. For each individual quality criterion, image quality of VMIs and MD iodine images was rated as better than that of SECT images (p < 0.001 in each case). Noise texture and intensity were rated better in MD iodine images than in VMIs. Conclusion: DECT using both DLIR and MAR for the generation of VMIs and MD iodine images resulted in higher subjective quality of oncologic head and neck images than ASIR-V-based SECT. Noise reduction and noise texture were best achieved with DLIR-based MD iodine images.

关键词： Computed tomography computer-assisted image processing Deep-learning image reconstruction Head and neck neoplasms

来源：评论

学校读者我要写书评

暂无评论

Automatic Brain Segmentation in Time-of-Flight MRA images

引用

METHODS OF INFORMATION IN MEDICINE 2009年第5期48卷 399-407页

作者： Forkert, N. D. Saering, D. Fiehler, J. Illiesz, T. Moeller, D. Handels, H. Univ Med Ctr Hamburg Eppendorf Dept Med Informat D-20246 Hamburg Germany Univ Med Ctr Hamburg Eppendorf Dept Diagnost & Intervent Neuroradiol D-20246 Hamburg Germany Univ Hamburg Fac Math Informat & Nat Sci Dept Comp Engn Hamburg Germany

Objectives: Cerebral vascular malformations might, caused by ruptures, lead to strokes. The rupture risk depends to a great extent on the individual anatomy of the vasculature. The 3D Time-of-Flight (TOF) MRA technique is one of the most commonly used non-invasive imaging techniques to obtain knowledge about the individual vascular anatomy. Unfortunately TOF images exhibit drawbacks for segmentation and direct volume visualization of the vasculature. To overcome these drawbacks an initial segmentation of the brain tissue is required. Methods: After preprocessing of the data is applied the low-intensity tissues surrounding the brain are segmented using region growing. In a following step this segmentation is used to extract supporting points at the border of the brain for a graph-based contour extraction. Finally a consistency check is performed to identify local outliers which are corrected using non-linear registration. Results: A quantitative validation of the method proposed was performed on 18 clinical datasets based on manual segmentations. A mean Dice coefficient of 0.989 was achieved while in average 99.56% of all vessel voxels were included by the brain segmentation. A comparison to the results yielded by three commonly used tools for brain segmentation revealed that the method described achieves better results, using TOF images as input, which are within the interobserver variability. Conclusion: The method suggested allows a robust and automatic segmentation of brain tissue in TOF images. It is especially helpful to improve the automatic segmentation or direct volume rendering of the cerebral vascular system.

关键词： computer-assisted image processing brain vascular disorders brain image segmentation magnetic resonance angiography

来源：评论

学校读者我要写书评

暂无评论

A comparative study of the effectiveness of photogrammetric versus manual anthropometric measurements

引用

WORK-A JOURNAL OF PREVENTION ASSESSMENT & REHABILITATION 2024年第3期78卷 735-746页

作者： Pal, Anubhab Patel, Thaneswer Khro, Keneiselie North Eastern Reg Inst Sci & Technol NERIST Dept Agr Engn Nirjuli 791109 Arunachal Prade India

BACKGROUND: The accurate measurement of the human body is essential when it comes to designing agricultural tools and equipment that can effectively accommodate and interact with individuals when performing a task. The traditional method for measuring an individual's body measurements is highly complex and requires two or more skilled individuals and reliable measurement tools. Finding a new approach that is speedier, more precise, and less expensive than current methods is therefore necessary. OBJECTIVE: This study aims to develop an inexpensive novel photogrammetric anthropometric measurement setup that can extract the dimensions of an individual subject irrespective of their body shape. METHODS: This study involved the creation of a setup comprising four cameras for a 360 degrees photoshoot of human subjects to calibrate and test the developed measurement setup for capturing photos of human subjects and compare the results with manual measurements. RESULTS: Ten different body dimensions were measured using the setup. There was a significant correlation between the manual and photogrammetric measurement methods (0.943 < r < 0.997). The highest absolute error recorded was 1.87%. CONCLUSION: The photogrammetric method for collecting anthropometric data is a reliable substitute for manual measurements across diverse populations. The results indicate that this low-cost approach is highly precise and reliable, with strong correlation to manual measurements. Multiview photogrammetry proves effective for individuals of various body shapes, making it a versatile option for data collection.

关键词： Photogrammetry computer-assisted image processing body size agricultural tools precision measurement

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence and machine learning in oncologic imaging

引用

Best Practice Onkologie 2021年第4期16卷 176-185页

作者： Kleesiek, J. Murray, J.M. Strack, C. Prinz, S. Kaissis, G. Braren, R. AG Computational Radiology Department of Radiology German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany Institut für Künstliche Intelligenz in der Medizin (IKIM) Universitätsklinikum Essen Girardetstr. 6 Essen 45131 Germany Heidelberg University Heidelberg Germany Department of Diagnostic and Interventional Radiology School of Medicine Technical University of Munich München Germany

Machine learning (ML) is entering many areas of society, including medicine. This transformation has the potential to drastically change medicine and medical practice. These aspects become particularly clear when considering the different stages of oncologic patient care and the involved interdisciplinary and intermodality interactions. In recent publications, computers—in collaboration with humans or alone—have been outperforming humans regarding tumor identification, tumor classification, estimating prognoses, and evaluation of treatments. In addition, ML algorithms, e.g., artificial neural networks (ANNs), which constitute the drivers behind many of the latest achievements in ML, can deliver this level of performance in a reproducible, fast, and inexpensive manner. In the future, artificial intelligence applications will become an integral part of the medical profession and offer advantages for oncologic diagnostics and treatment. © 2021, Springer Medizin Verlag GmbH, ein Teil von Springer Nature.

关键词： computer-assisted image processing Deep learning Diagnostic imaging Machine learning Neural networks (computer)

来源：评论

学校读者我要写书评

暂无评论

AutoTag and AutoSnap: Standardized, semi-automatic capture of regions of interest from whole slide images

引用

METHODSX 2015年 2卷 272-277页

作者： Marien, Koen M. Andries, Luc De Schepper, Stefanie Kockx, Mark M. De Meyer, Guido R. Y. Univ Antwerp Lab Physiopharmacol Univ Pl 1 B-2610 Antwerp Belgium HistoGeneX NV ZNA Middelheim CampusLindendreef 1 B-2020 Antwerp Belgium

Tumor angiogenesis is measured by counting microvessels in tissue sections at high power magnification as a potential prognostic or predictive biomarker. Until now, regions of interest(1) (ROls) were selected by manual operations within a tumor by using a systematic uniform random sampling(2) (SURS) approach. Although SURS is the most reliable sampling method, it implies a high workload. However, SURS can be semi-automated and in this way contribute to the development of a validated quantification method for microvessel counting in the clinical setting. Here, we report a method to use semi-automated SURS for microvessel counting: Whole slide imaging with Pannoramic SCAN (3DHISTECH) computer-assisted sampling in Pannoramic Viewer (3DHISTECH) extended by two self-written AutoHotkey applications (AutoTag and AutoSnap) The use of digital grids in Photoshop (R)) and Bridge (R) (Adobe Systems) This rapid procedure allows traceability essential for high throughput protein analysis of immunohistochemically stained tissue. (C) 2015 The Authors. Published by Elsevier B.V.

关键词： Microvessels computer-assisted image processing Selection bias Automation Stereology Whole slide image

来源：评论

学校读者我要写书评

暂无评论

A Block-matching based technique for the analysis of 2D gel images 13

A Block-matching based technique for the analysis of 2D gel ...

引用

13th World Congress on Medical and Health Informatics of International-Medical-Informatics-Association (Medinfo)

作者： Freire, Ana Seoane, Jose A. Rodriguez, Alvaro Ruiz-Romero, Cristina Lopez-Campos, Guillermo Dorado, Julian Univ A Coruna Fac Comp Sci Informat & Commun Technol Dept La Coruna Spain CHUAC La Coruna Spain Inst Hlth Carlos III Bioinformat & Publ Hlth Unit Madrid Spain Biomed Res Inst A Coruna INIBIC La Coruna Spain

ISBN: (纸本)9781607505884

Research at protein level is a useful practice in personalized medicine. More specifically, 2D gel images obtained after electrophoresis process can lead to an accurate diagnosis. Several computational approaches try to help the clinicians to establish the correspondence between pairs of proteins of multiple 2D gel images. Most of them perform the alignment of a patient image referred to a reference image. In this work, an approach based on block-matching techniques is developed. Its main characteristic is that it does not need to perform the whole alignment between two images considering each protein separately. A comparison with other published methods is presented. It can be concluded that this method works over broad range of proteomic images, although they have a high level of difficulty.

关键词： 2-D gel electrophoresis Block-matching Proteomics computer-assisted image processing

来源：评论

学校读者我要写书评

暂无评论

Assessment of three methods of geometric image reconstruction for digital subtraction radiography

引用

DENTOMAXILLOFACIAL RADIOLOGY 2016年第7期45卷 20160120-20160120页

作者： Queiroz, Polyane M. Oliveira, Matheus L. Tanaka, Jefferson L. Soares, Milton G. Haiter-Neto, Francisco Ono, Evelise Univ Estadual Campinas Dept Oral Diag Area Oral Radiol Piracicaba Dent Sch Sao Paulo Brazil Brazilian Dent Assoc Dept Dent Radiol & Imaging Ponta Grosso Parana Brazil Univ Estadual Londrina Dept Oral Med Londrina Parana Brazil

Objectives: To evaluate three methods of geometric image reconstruction for digital subtraction radiography (DSR). Methods: Digital periapical radiographs were acquired. of 24 teeth with the X-ray tube at 6 different geometric configurations of vertical (V) and horizontal (H) angles: V0 degrees H0 degrees, V0 degrees H10 degrees, V10 degrees H0 degrees, V10 degrees H10 degrees, V20 degrees H0 degrees and V20 degrees H10 degrees. All 144 images were registered in pairs (Group V0 degrees H0 degrees + 1 of the 6 groups) 3 times by using the Emago((R)) (Oral Diagnostic Systems, Amsterdam, Netherlands) with manual selection and Regeemy with manual and automatic selections. After geometric reconstruction on the two software applications under different modes of selection, all images were subtracted and the standard deviation of grey values was obtained as a measure of image noise. All measurements were repeated after 15 days to evaluate the method error. Values of image noise were statistically analyzed by one-way ANOVA for differences between methods and between projection angles, followed by Tukey's test at a level of significance of 5%. Results: Significant differences were found between most of the projection angles for the three reconstruction methods. image subtraction after manual selection-based reconstruction on Regeemy presented the lowest values of image noise, except on group V0 degrees H0 degrees. The groups V10 degrees H0 degrees and V20 degrees H0 degrees were not significantly different between the manual selection-based reconstruction in Regeemy and automatic selection-based reconstruction in Regeemy methods. Conclusions: The Regeemy software on manual mode revealed better quality of geometric image reconstruction for DSR than the Regeemy on automatic mode and the Emago on manual mode, when the radiographic images were obtained at V and H angles used in the present investigation.

关键词： digital dental radiography radiographic image enhancement computer-assisted image processing

来源：评论

学校读者我要写书评

暂无评论

Mixed reality technology-initial experience from liver surgery

引用

GASTROENTEROLOGIE 2023年第1期18卷 46-53页

作者： Mero, G. Donchev, R. Banysch, M. Hornstein, M. Heuer, T. Kaiser, G. M. St Bernhard Hosp Klin Allgemein & Viszeralchirurgie Burgermeister Schmelzing Str 90 D-47475 Kamp Lintfort Germany St Bernhard Hosp Med Klin 1 Kamp Lintfort Germany

Background: Developments in imaging technology enable better diagnostics and, thus, also safer visceral interventions. One of the most recent developments is the use of mixed reality in the operating room, a "mixture " of reality with three-dimensional (3D) reconstructed preoperative images. Thus, we present our first experiences with the application of mixed reality in the field of liver *** and methods: Eight patients (age 62-82 years) with primary liver malignancy (n = 4) or liver metastases (n = 4) were studied and documented in this work. The time required to fully prepare the preoperative reconstructions was analyzed and the benefits of the new technology were graded by the members of the treatment team for each case. We use an open-source software for image analysis and scientific visualization ***: The time required to prepare for the operation is considerable and relevant for the everyday clinical practice (150-360 min). We were able to gain more information about tumor location and the relationship to other important intra-abdominal structures preoperatively and intraoperatively through the use of the technology. We have not yet been able to demonstrate a benefit in the area of risk minimization for the patient, faster operation times or faster recovery in this ***: Mixed reality technology offers an enormous range of possible applications. In particular, it has great potential for visceral surgery, patient education, but also medical training. Further investigations are necessary to more precisely assess the advantages and disadvantages in larger case series.

关键词： Liver neoplasms Neoplasm metastasis Information science computer-assisted image processing computer simulation

来源：评论

学校读者我要写书评

暂无评论

Computed Quality Assessment of MPEG4-compressed DICOM Video Data

Computed Quality Assessment of MPEG4-compressed DICOM Video ...

引用

19th International Congress of the European-Federation-for-Medical-Informatics

作者： Frankewitsch, Thomas Soehnlein, Sven Mueller, Marcel Prokosch, Hans-Ulrich Univ Erlangen Nuernberg Dept Med Informat Erlangen Germany

ISBN: (纸本)9781586035495

Digital Imaging and Communication in Medicine (DICOM) has become one of the most popular standards in medicine. This standard specifies the exact procedures in which digital images are exchanged between devices, either using a network or storage medium. Sources for images vary;therefore there exist definitions for the exchange for CR, CT, NMR, angiography, sonography and so on. With its spreading, with the increasing amount of sources included, data volume is increasing, too. This affects storage and traffic. While for long-time storage data compression is generally not accepted tit the moment, there are many situations where data compression is possible: Telemedicine for educational purposes (e.g, students at home using low speed internet connections), presentations with standard-resolution video projectors, or even the supply on wards combined receiving written findings. DICOM comprises compression: for still image there is JPEG, for video MPEG-2 is adopted. Within the last Years MPEG-2 has been evolved to MPEG-4, which squeezes data even better, bill the risk of significant errors increases, too. Within the last years effects of compression have been analyzed for entertainment movies, but these are not comparable. to videos of physical examinations (e.g. echocardiography). In medical videos an individual image plays a more important role. Erroneous single images affect total quality even more. Additionally, the effect of compression can Plot be generalized from one test series to all videos. The result depends strongly on the source. Some investigations have been presented, where different MPEG-4 algorithms compressed videos have been compared and rated manually. But they describe only the results in all elected testbed. In this paper some methods derived from video rating are presented and discussed for an automatically created quality control for the compression of medical videos, primary stored in DICOM containers.

关键词： computer-assisted image processing Telemedicine Coronary Angiography Quality Control

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：