检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

3,922 篇 会议
108 篇 期刊文献
80 册 图书

馆藏范围

4,109 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

3,628 篇 工学
- 3,283 篇 计算机科学与技术...
- 1,893 篇 生物医学工程（可授...
- 1,553 篇 软件工程
- 992 篇 光学工程
- 501 篇 生物工程
- 379 篇 电气工程
- 319 篇 电子科学与技术（可...
- 269 篇 信息与通信工程
- 201 篇 控制科学与工程
- 157 篇 仪器科学与技术
- 63 篇 核科学与技术
- 45 篇 力学（可授工学、理...
- 37 篇 安全科学与工程
- 36 篇 化学工程与技术
- 34 篇 机械工程
- 28 篇 建筑学
2,707 篇 医学
- 1,923 篇 特种医学
- 1,682 篇 临床医学
- 666 篇 基础医学(可授医学...
- 466 篇 药学(可授医学、理...
- 322 篇 医学技术（可授医学...
- 62 篇 公共卫生与预防医...
1,105 篇 理学
- 573 篇 生物学
- 516 篇 物理学
- 482 篇 数学
- 143 篇 统计学（可授理学、...
- 60 篇 化学
141 篇 管理学
- 94 篇 图书情报与档案管...
- 50 篇 管理科学与工程(可...
30 篇 教育学
- 30 篇 教育学
9 篇 农学
7 篇 经济学
6 篇 法学
1 篇 军事学

主题

334 篇 image segmentati...
183 篇 magnetic resonan...
181 篇 deep learning
161 篇 medical imaging
129 篇 image registrati...
84 篇 image enhancemen...
79 篇 segmentation
76 篇 image reconstruc...
71 篇 medical image se...
68 篇 computerized tom...
66 篇 artificial intel...
59 篇 image processing...
54 篇 deformation
52 篇 pattern recognit...
49 篇 image classifica...
48 篇 convolutional ne...
46 篇 magnetic resonan...
45 篇 semi-supervised ...
42 篇 contrastive lear...
41 篇 image analysis

机构

31 篇 ucl ctr med imag...
21 篇 queens univ sch ...
21 篇 imperial coll lo...
20 篇 shenzhen univ ma...
19 篇 kings coll londo...
19 篇 simon fraser uni...
19 篇 shenzhen univ me...
17 篇 ucl ctr med imag...
17 篇 chinese univ hon...
16 篇 tencent jarvis l...
15 篇 centre for medic...
15 篇 shanghai united ...
15 篇 department of co...
15 篇 univ n carolina ...
14 篇 national center ...
14 篇 shanghai jiao to...
14 篇 harvard med sch ...
13 篇 biomedical image...
13 篇 univ penn dept r...
13 篇 shanghaitech uni...

作者

93 篇 rueckert daniel
76 篇 navab nassir
71 篇 shen dinggang
50 篇 ourselin sebasti...
48 篇 hamarneh ghassan
44 篇 yang guang-zhong
33 篇 zheng yefeng
31 篇 ni dong
29 篇 duncan james s.
29 篇 zhou s. kevin
28 篇 glocker ben
26 篇 yang xin
25 篇 comaniciu dorin
25 篇 abugharbieh rafe...
25 篇 zheng guoyan
24 篇 yap pew-thian
24 篇 fichtinger gabor
23 篇 golland polina
23 篇 abolmaesumi pura...
22 篇 collins d. louis

语言

4,057 篇 英文
50 篇 其他
8 篇 中文

检索条件"任意字段=3rd International Conference on Medical Image Computing and Computer-Assisted Intervention"

共 4110 条记录，以下是31-40 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

11th international Workshop on Machine Learning in medical Imaging, MLMI 2020, held in conjunction with the 23rd international conference on medical image computing and computer assisted intervention, MICCAI 2020

11th International Workshop on Machine Learning in Medical I...

引用

11th international Workshop on Machine Learning in medical Imaging, MLMI 2020, held in conjunction with the 23rd international conference on medical image computing and computer assisted intervention, MICCAI 2020

ISBN: (纸本)9783030598600

The proceedings contain 68 papers. The special focus in this conference is on Machine Learning in medical Imaging. The topics include: Out-of-Distribution Detection for Skin Lesion images with Deep Isolation Forest;A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation;Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network;robust Multiple Sclerosis Lesion Inpainting with Edge Prior;segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation;GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes;anatomy-Aware Cardiac Motion Estimation;division and Fusion: Rethink Convolutional Kernels for 3D medical image Segmentation;LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI;Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation;error Attention Interactive Segmentation of medical image Through Matting and Fusion;boundary-Aware Network for Kidney Tumor Segmentation;o-Net: An Overall Convolutional Network for Segmentation Tasks;label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints;eczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis;deep Distance Map Regression Network with Shape-Aware Loss for Imbalanced medical image Segmentation;Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer;exploring Functional Difference Between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks;detection of Ischemic Infarct Core in Non-contrast Computed Tomography;bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers;extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients;A Novel fMRI Representation Learning Framework with GAN;structural Connectivity Enriched Functional Brain Network U

关键词：

来源：评论

学校读者我要写书评

暂无评论

1st international Workshop on Advances in Simplifying medical UltraSound, ASMUS 2020, and the 5th international Workshop on Perinatal, Preterm and Paediatric image Analysis, PIPPI 2020, held in conjunction with the 23rd international conference on medical image computing and computer-assisted intervention, MICCAI 2020

1st International Workshop on Advances in Simplifying Medica...

引用

1st international Workshop on Advances in Simplifying medical UltraSound, ASMUS 2020, and the 5th international Workshop on Perinatal, Preterm and Paediatric image Analysis, PIPPI 2020, held in conjunction with the 23rd international conference on medical image computing and computer-assisted intervention, MICCAI 2020

ISBN: (纸本)9783030603335

The proceedings contain 33 papers. The special focus in this conference is on Advances in Simplifying medical UltraSound. The topics include: Localizing 2D Ultrasound Probe from Ultrasound image Sequences Using Deep Learning for Volume Reconstruction;augmented Reality-Based Lung Ultrasound Scanning Guidance;multimodality Biomedical image Registration Using Free Point Transformer Networks;label Efficient Localization of Fetal Brain Biometry Planes in Ultrasound Through Metric Learning;automatic C-Plane Detection in Pelvic Floor Transperineal Volumetric Ultrasound;unsupervised Cross-domain image Classification by Distance Metric Guided Feature Alignment;dual-Robotic Ultrasound System for In Vivo Prostate Tomography;IoT-Based Remote Control Study of a Robotic Trans-Esophageal Ultrasound Probe via LAN and 5G;differentiating Operator Skill During Routine Fetal Ultrasound Scanning Using Probe Motion Tracking;kinematics Data Representations for Skills Assessment in Ultrasound-Guided Needle Insertion;calibrated Bayesian Neural Networks to Estimate Gestational Age and Its Uncertainty on Fetal Brain Ultrasound images;3D Fetal Pose Estimation with Adaptive Variance and Conditional Generative Adversarial Network;atlas-Based Segmentation of the Human Embryo Using Deep Learning with Minimal Supervision;Deformable Slice-to-Volume Registration for Reconstruction of Quantitative T2* Placental and Fetal MRI;a Smartphone-Based System for Real-Time Early Childhood Caries Diagnosis;automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening;Harmonised Segmentation of Neonatal Brain MRI: A Domain Adaptation Approach;a Multi-task Approach Using Positional Information for Ultrasound Placenta Segmentation;spontaneous Preterm Birth Prediction Using Convolutional Neural Networks;Multi-modal Perceptual Adversarial Learning for Longitudinal Prediction of Infant MR images;Efficient Multi-class Fetal Brain Segmentation in High Resolution MRI Reconstructions with Noisy Labels.

关键词：

来源：评论

学校读者我要写书评

暂无评论

1st Myocardial Pathology Segmentation Combining Multi-Sequence CMR Challenge, MyoPS 2020 held in conjunction with 23rd international conference on medical image computing and computer-assisted intervention, MICCAI 2020

1st Myocardial Pathology Segmentation Combining Multi-Sequen...

引用

1st Myocardial Pathology Segmentation Combining Multi-Sequence CMR Challenge, MyoPS 2020 held in conjunction with 23rd international conference on medical image computing and computer-assisted intervention, MICCAI 2020

ISBN: (纸本)9783030656508

The proceedings contain 16 papers. The special focus in this conference is on Myocardial Pathology Segmentation Combining Multi-Sequence CMR Challenge. The topics include: Two-Stage Method for Segmentation of the Myocardial Scars and Edema on Multi-sequence Cardiac Magnetic Resonance;efficientSeg: A Simple But Efficient Solution to Myocardial Pathology Segmentation Challenge;Recognition and Standardization of Cardiac MRI Orientation via Multi-tasking Learning and Deep Neural Networks;Cascaded Framework with Complementary CMR Information for Myocardial Pathology Segmentation;Dual-Path Feature Aggregation Network Combined Multi-layer Fusion for Myocardial Pathology Segmentation with Multi-sequence Cardiac MR;stacked and Parallel U-Nets with Multi-output for Myocardial Pathology Segmentation;accurate Myocardial Pathology Segmentation with Residual U-Net;Dual Attention U-Net for Multi-sequence Cardiac MR images Segmentation;Automatic Myocardial Scar Segmentation from Multi-sequence Cardiac MRI Using Fully Convolutional Densenet with Inception and Squeeze-Excitation Module;exploring Ensemble Applications for Multi-sequence Myocardial Pathology Segmentation;preface;Stacked BCDU-Net with Semantic CMR Synthesis: Application to Myocardial Pathology Segmentation Challenge;CMS-UNet: Cardiac Multi-task Segmentation in MRI with a U-Shaped Network;Fully Automated Deep Learning Based Segmentation of Normal, Infarcted and Edema Regions from Multiple Cardiac MRI Sequences.

关键词：

来源：评论

学校读者我要写书评

暂无评论

9th international Workshop on Brain Lesion workshop, BrainLes 2023 and 3rd Stroke Workshop on Imaging and Treatment CHallenges, SWITCH 2023 Held in Conjunction with 26th medical image computing and computer assisted intervention, MICCAI 2023

9th International Workshop on Brain Lesion workshop, BrainLe...

引用

9th international Workshop on Brain Lesion workshop, BrainLes 2023 and 3rd Stroke Workshop on Imaging and Treatment CHallenges, SWITCH 2023 Held in Conjunction with 26th medical image computing and computer assisted intervention, MICCAI 2023

ISBN: (纸本)9783031761591

The proceedings contain 15 papers. The special focus in this conference is on Imaging and Treatment CHallenges. The topics include: BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision;towards Radiomics-Based Automated Disease Progression Assessment for Glioblastoma Patients;Domain Unlearning Boosts Lesion Segmentation Performance on Seen and Unseen MR Scanner Data;primitive Simultaneous Optimization of Similarity Metrics for image Registration;reFuSeg: Regularized Multi-modal Fusion for Precise Brain Tumour Segmentation;3D MRI Brain Tumor Diagnosis with Topological Descriptors;an Automatic Cascaded Model for Hemorrhagic Stroke Segmentation and Hemorrhagic Volume Estimation;Deep Learning for Ischemic Penumbra Segmentation from MR Perfusion Maps: Robustness to the Deconvolution Algorithm;from Brain Tissue Infarction at 24 Hours to Patient Functional Outcome at 90 Days Using Deep Learning;functional Outcome Prediction in Acute Ischemic Stroke;the Detection and Segmentation of Blush in the Lenticulostriate Territory;multimodal Deep Learning for Functional Outcome Prediction in Endovascular Therapy;Framework to Generate Perfusion Map from CT and CTA images in Patients with Acute Ischemic Stroke: A Longitudinal and Cross-Sectional Study.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2nd international Workshop on Fairness of AI in medical Imaging, FAIMI 2024, and 3rd international Workshop on Ethical and Philosophical Issues in medical Imaging, EPIMI 2024, Held in Conjunction with the international conference on medical image computing and computer assisted interventions, MICCAI 2024

2nd International Workshop on Fairness of AI in Medical Imag...

引用

2nd international Workshop on Fairness of AI in medical Imaging, FAIMI 2024, and 3rd international Workshop on Ethical and Philosophical Issues in medical Imaging, EPIMI 2024, Held in Conjunction with the international conference on medical image computing and computer assisted interventions, MICCAI 2024

ISBN: (纸本)9783031727863

The proceedings contain 17 papers. The special focus in this conference is on Fairness of AI in medical Imaging. The topics include: Dataset Distribution Impacts Model Fairness: Single Vs. Multi-task Learning;AI Fairness in medical Imaging: Controlling for Disease Severity;Fair and Private CT Contrast Agent Detection;Mitigating Overdiagnosis Bias in CNN-Based Alzheimer’s Disease Diagnosis for the Elderly;Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains;all You Need Is a Guiding Hand: Mitigating Shortcut Bias in Deep Learning Models for medical Imaging;exploring Fairness in State-of-the-Art Pulmonary Nodule Detection Algorithms;quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation;BMFT: Achieving Fairness via Bias-Based Weight Masking Fine-Tuning;using Backbone Foundation Model for Evaluating Fairness in Chest Radiography Without Demographic Data;do Sites Benefit Equally from Distributed Learning in medical image Analysis?;Cycle-GANs Generated Difference Maps to Interpret Race Prediction from medical images;On Biases in a UK Biobank-Based Retinal image Classification Model;investigating Gender Bias in Lymph-Node Segmentation with Anatomical Priors;Assessing the Impact of Sociotechnical Harms in AI-Based medical image Analysis;Practical and Ethical Considerations for Generative AI in medical Imaging.

关键词：

来源：评论

学校读者我要写书评

暂无评论

1st Workshop on Topology- and Graph- Informed Imaging Informatics, TGI3 2024, held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

1st Workshop on Topology- and Graph- Informed Imaging Inform...

引用

1st Workshop on Topology- and Graph- Informed Imaging Informatics, TGI3 2024, held in conjunction with the 27th international conference on medical image computing and computer assisted intervention, MICCAI 2024

ISBN: (纸本)9783031739668

The proceedings contain 13 papers. The special focus in this conference is on Topology- and Graph- Informed Imaging Informatics. The topics include: TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis;analyzing Brain Tumor Connectomics Using Graphs and Persistent Homology;a Bispectral 3D U-Net for Rotation Robustness in medical Segmentation;restoring Connectivity in Vascular Segmentations Using a Learned Post-processing Model;multi-factor Component Tree Loss Function: A Topology-Preserving Method for Skeleton Segmentation from Bone Scintigrams;exploitation of Mapper Algorithm in Neuroimaging Applications: A Novel Framework for Outcomes Prediction;Topological Data Analysis of Resting-State fMRI Suggests Altered Brain Network Topology in Functional Dyspepsia: A Mapper-Based Parcellation Approach;P-Count: Persistence-Based Counting of White Matter Hyperintensities in Brain MRI;Outlier Detection in Large Radiological Datasets Using UMAP;a Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging;topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity.

关键词：

来源：评论

学校读者我要写书评

暂无评论

3rd international Workshop on Patch-Based Techniques in medical Imaging, Patch-MI 2017 held in conjunction with 20th international conference on medical image computing and computer assisted intervention, MICCAI 2017

3rd International Workshop on Patch-Based Techniques in Medi...

引用

3rd international Workshop on Patch-Based Techniques in medical Imaging, Patch-MI 2017 held in conjunction with 20th international conference on medical image computing and computer assisted intervention, MICCAI 2017

ISBN: (纸本)9783319674339

The proceedings contain 18 papers. The special focus in this conference is on Patch-Based Techniques in medical Imaging. The topics include: 4D multi-atlas label fusion using longitudinal images;brain image labeling using multi-atlas guided 3d fully convolutional networks;validation on ventriculomegaly patients;hippocampus subfield segmentation using a patch-based boosted ensemble of autocontext neural networks;on the role of patch spaces in patch-based label fusion;learning a sparse database for patch-based medical image segmentation;accurate and high throughput cell segmentation method for mouse brain nuclei using cascaded convolutional neural network;learning-based estimation of functional correlation tensors in white matter for early diagnosis of mild cognitive impairment;early prediction of Alzheimer’s disease with non-local patch-based longitudinal descriptors;adaptive fusion of texture-based grading: application to Alzheimer’s disease detection;micro-CT guided 3D reconstruction of histological images;a dictionary learning-based fast imaging method for ultrasound elastography;breast tumor detection in ultrasound images using deep learning;modeling the intra-class variability for liver lesion detection using a multi-class patch-based CNN;multiple sclerosis lesion segmentation using joint label fusion;deep multimodal case–based retrieval for large histopathology datasets and sparse representation using block decomposition for characterization of imaging patterns.

关键词：

来源：评论

学校读者我要写书评

暂无评论

3rd international Workshop on Deep Learning in medical image Analysis, DLMIA 2017 and 7th international Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th international conference on medical image computing and computer assisted intervention, MICCAI 2017

3rd International Workshop on Deep Learning in Medical Image...

引用

3rd international Workshop on Deep Learning in medical image Analysis, DLMIA 2017 and 7th international Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th international conference on medical image computing and computer assisted intervention, MICCAI 2017

ISBN: (纸本)9783319675572

The proceedings contain 43 papers. The special focus in this conference is on Deep Learning in medical image Analysis. The topics include: Simultaneous multiple surface segmentation using deep learning;a deep residual inception network for HEp-2 cell classification;joint segmentation of multiple thoracic organs in CT images with two collaborative deep architectures;accelerated magnetic resonance imaging by adversarial neural network;left atrium segmentation in CT volumes with fully convolutional networks;3d randomized connection network with graph-based inference;adversarial training and dilated convolutions for brain mri segmentation;CNNs enable accurate and fast segmentation of drusen in optical coherence tomography;domain-adversarial neural networks to address the appearance variability of histopathology images;accurate lung segmentation via network-wise training of convolutional networks;computationally efficient cardiac views projection using 3d convolutional neural networks;a deep level set method for image segmentation;context-based normalization of histological stains using deep convolutional features;transitioning between convolutional and fully connected layers in neural networks;pathological pulmonary lobe segmentation from CT images using progressive holistically nested neural networks and random walker;stain colour normalisation to improve mitosis detection on breast histology images;a unified framework for tumor proliferation score prediction in breast histopathology and generalised dice overlap as a deep learning loss function for highly unbalanced segmentations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

1st international Workshop on Graphs in Biomedical image Analysis, GRAIL 2017, 6th international Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd international Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th international conference on medical image computing and computer assisted intervention, MICCAI 2017

1st International Workshop on Graphs in Biomedical Image Ana...

引用

1st international Workshop on Graphs in Biomedical image Analysis, GRAIL 2017, 6th international Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd international Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th international conference on medical image computing and computer assisted intervention, MICCAI 2017

ISBN: (纸本)9783319676746

The proceedings contain 22 papers. The special focus in this conference is on Graphs in Biomedical image Analysis. The topics include: Classifying phenotypes based on the community structure of human brain networks;autism spectrum disorder diagnosis using sparse graph embedding of morphological brain networks;topology of surface displacement shape feature in subcortical structures;graph geodesics to find progressively similar skin lesion images;uncertainty estimation in vascular networks;extraction of airways with probabilistic state-space models and bayesian smoothing;detection and localization of landmarks in the lower extremities using an automatically learned conditional random field;bridge simulation and metric estimation on landmark manifolds;white matter fiber segmentation using functional varifolds;a new metric for statistical analysis of rigid transformations;unbiased diffeomorphic mapping of longitudinal data with simultaneous subject specific template estimation;exact function alignment under elastic riemannian metric;varifold-based matching of curves via sobolev-type riemannian metrics;computational anatomy in theano;rank constrained diffeomorphic density motion estimation for respiratory correlated computed tomography;efficient parallel transport in the group of diffeomorphisms via reduction to the lie algebra;multilevel modeling with structured penalties for classification from imaging genetics data and coupled dimensionality-reduction model for imaging genomics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2nd international ToothFairy2: Multi-Structure Segmentation in CBCT Volumes, ToothFairy 2024, 3D Teeth Landmarks Detection Challenge, 3DTeethLand 2024, Semi-supervised Teeth Segmentation, STS 2024 held in conjunction with the 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

2nd International ToothFairy2: Multi-Structure Segmentation ...

引用

2nd international ToothFairy2: Multi-Structure Segmentation in CBCT Volumes, ToothFairy 2024, 3D Teeth Landmarks Detection Challenge, 3DTeethLand 2024, Semi-supervised Teeth Segmentation, STS 2024 held in conjunction with the 27th international conference on medical image computing and computer-assisted intervention, MICCAI 2024

ISBN: (纸本)9783031889769

The proceedings contain 21 papers. The special focus in this conference is on medical image computing and computer-assisted intervention. The topics include: Inferior Alveolar Nerve Segmentation in CBCT images Using Connectivity-Based Selective Re-training;Scaling nnU-Net for CBCT Segmentation;DiENTeS: Dynamic ENTity Segmentation with Local-Global Transformers;Enhanced Multi-structure Segmentation in CBCT images with Adaptive Structure Optimization;Weakly-Supervised Convolutional Neural Networks for Inferior Alveolar Nerve Segmentation in CBCT images;a Multi-Axial Network for Oral Structure Segmentation;automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures;video Foundation Model for medical 3D Segmentation;a Two-Stage Semi-supervised nnU-Net Model for Automated Tooth Segmentation in Panoramic X-Ray images;Two-Stage Semi-supervised nnU-Net Framework for Tooth Segmentation in CBCT images;SemiT-SAM: Building A Visual Foundation Model for Tooth Instance Segmentation on Panoramic Radiographs;Multi-stage Dental Visual Detection Based on YOLOv8: Dental 3D CBCT;Efficient Semi-supervised Tooth Instance Segmentation in Panoramic X-Rays Using ResUnet50 and SAM Networks;DAE-Net: Dual Attention Embedding-Based Tooth Instance Segmentation Approach for Panoramic X-Ray images;a Self-training Pipeline for Semi-supervised 2D Teeth Instance Segmentation;deformable Inherent Consistent Learning Network for Accurate Tooth Segmentation in Dental Panoramic Radiographs;semi-supervised 2D Dental image Segmentation via Cross Teaching Network;a Novel Two-Stage Approach for 3D Dental Tooth Instance Segmentation;a Two-Stage Framework with Dual-Branch Network for End-to-End 3D Tooth Landmark Detection;leveraging Point Transformers for Detecting Anatomical Landmarks in Digital Dentistry;toothInstanceNet: Comprehensive Information from Intra-oral Scans by Integration of Large-Context and High-Resolution Predictions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共411页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：