2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)最新文献_第6页

Spatially-Preserving Flattening for Location-Aware Classification of Findings in Chest X-Rays 保留空间的平坦化方法在胸部x射线中定位感知分类

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761630

Neha Srivathsa, Razi Mahmood, T. Syeda-Mahmood

引用次数: 0

TDM-Stargan: Stargan Using Time Difference Map to Generate Dynamic Contrast-Enhanced Mri from Ultrafast Dynamic Contrast-Enhanced Mri TDM-Stargan: Stargan利用时差图从超快动态增强Mri生成动态增强Mri

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761463

Young-Tack Oh, Eunsook Ko, Hyunjin Park

引用次数: 1

Faster R-CNN for IPSC-Derived Mesenchymal Stromal Cells Senescent Detection from Bright-Field Microscopy 基于R-CNN的ipsc间充质间质细胞衰老检测

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761548

Mingzhu Li, Liang He, Xinglie Wang, Tianfu Wang, Guanghui Yue, Guangqian Zhou, Baiying Lei

引用次数: 0

Transformer Graph Network for Coronary Plaque Localization in CCTA 变换图网络在冠状动脉斑块定位中的应用

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761646

Mario Viti, H. Talbot, N. Gogin

{"title":"Transformer Graph Network for Coronary Plaque Localization in CCTA","authors":"Mario Viti, H. Talbot, N. Gogin","doi":"10.1109/ISBI52829.2022.9761646","DOIUrl":"https://doi.org/10.1109/ISBI52829.2022.9761646","url":null,"abstract":"Coronary CT angiography (CCTA) is the only non-invasive imaging technique that reliably depicts the anatomic extent of Coronary Artery Disease (CAD). While occlusion remains a highly predictive indicator of major cardiovascular events (MACE), there is growing evidence that the presence and characteristics of coronary atherosclerosis provide additional prognostic information. In CCTA calcified plaques display high-intensity Hounsfield Units (HU) representative features while more complex representations characterize high-risk soft plaques. As such, accurate identification and quantification is burdensome and time consuming because of the limited temporal, spatial and contrast resolutions of X-ray scanners. Despite the success of deep learning in medical imaging, automatic localization of coronary plaques and especially soft plaques remains a challenging subject in CCTA vessel analysis. For this study, 150 CCTA scans were retrospectively collected. All patients were accepted at triage with minimal to severe CAD suspicion. Selection was carried out with uniform CAD-RADS severity distribution which normally follows an exponential decay function, thus obtaining a higher than normal concentration of plaques. The proposed method outperforms the state of the art for the localization of diverse types of plaques by exploiting the self-attention mechanism of transformers networks to embed contextual features of the coronary tree.","PeriodicalId":6827,"journal":{"name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","volume":"52 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79044445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Differentiable Projection from Optical Coherence Tomography B-Scan without Retinal Layer Segmentation Supervision 无视网膜层分割监督下光学相干断层b扫描的可微投影

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761656

Dingyi Rong, Jiancheng Yang, Bingbing Ni, B. Ke

引用次数: 0

Generation of 12-Lead Electrocardiogram with Subject-Specific, Image-Derived Characteristics Using a Conditional Variational Autoencoder 使用条件变分自编码器生成具有受试者特定图像衍生特征的12导联心电图

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761431

Yuling Sang, M. Beetz, V. Grau

引用次数: 3

Quantifying Newly Appearing Replication FOCI in Cell Nuclei Based on 3d Non-Rigid Registration 基于三维非刚性配准的细胞核新出现的复制FOCI定量

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761689

Qi Gao, Vadim O. Chagin, M. C. Cardoso, K. Rohr

引用次数: 0

Active Index: An Integrated Index to Reveal Disrupted Brain Network Organizations of Major Depressive Disorder Patients 活跃指数:揭示重度抑郁症患者脑网络组织紊乱的综合指数

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761503

Yu Fu, Yanyan Huang, Meng Niu, Le Xue, Shunjie Dong, Shunlin Guo, J. Lei, Cheng Zhuo

{"title":"Active Index: An Integrated Index to Reveal Disrupted Brain Network Organizations of Major Depressive Disorder Patients","authors":"Yu Fu, Yanyan Huang, Meng Niu, Le Xue, Shunjie Dong, Shunlin Guo, J. Lei, Cheng Zhuo","doi":"10.1109/ISBI52829.2022.9761503","DOIUrl":"https://doi.org/10.1109/ISBI52829.2022.9761503","url":null,"abstract":"Altered functional brain networks have been a typical manifestation that distinguishes major depressive disorder (MDD) patients from healthy control (HC) subjects in functional magnetic resonance imaging (fMRI) studies. Recently, rich club and diverse club metrics have been proposed for network or network neuroscience analyses. The rich club defines a set of nodes that tend to be the hubs of specific communities, and the diverse club defines the nodes that span more communities and have edges diversely distributed across different communities. Considering the heterogeneity of rich clubs and diverse clubs, combining them and on the basis to derive a novel indicator may reveal new evidence of brain functional integration and separation, which might provide new insights into MDD. This study for the first time discussed the differences between MDD and HC using both rich club and diverse club metrics and found the complementarity of them in analyzing brain networks. Besides, a novel index, termed \"active index\", has been proposed in this study. The active index defines a group of nodes that tend to be diversely distributed across communities while avoiding being a hub of a community. Experimental results demonstrate the superiority of active index in analyzing MDD brain mechanisms.","PeriodicalId":6827,"journal":{"name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","volume":"133 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86330357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Joint Attention for Medical Image Segmentation 医学图像分割的联合关注

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761624

Mo Zhang, Bin Dong, Quanzheng Li

引用次数: 0

Automated Dcis Identification From Multiplex Immunohistochemistry Using Generative Adversarial Networks 利用生成对抗网络从多重免疫组化中自动识别Dcis

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) Pub Date : 2022-03-28 DOI: 10.1109/ISBI52829.2022.9761413

F. Sobhani, A. Hamidinekoo, A. Hall, Lorraine M. King, J. Marks, C. Maley, H. Horlings, E. Hwang, Yinyin Yuan

{"title":"Automated Dcis Identification From Multiplex Immunohistochemistry Using Generative Adversarial Networks","authors":"F. Sobhani, A. Hamidinekoo, A. Hall, Lorraine M. King, J. Marks, C. Maley, H. Horlings, E. Hwang, Yinyin Yuan","doi":"10.1109/ISBI52829.2022.9761413","DOIUrl":"https://doi.org/10.1109/ISBI52829.2022.9761413","url":null,"abstract":"Ductal Carcinoma In Situ (DCIS) is a non-obligatory precursor of Invasive Breast Cancer. It is the most common mammographically detected breast cancer. Predicting DCIS progression to invasive ductal carcinoma is a major clinical challenge due to the lack of a uniform classification system in the diagnosis and prognostication of this disease. To characterise the tissue microecology of DCIS, we proposed and tested the model \"DCIS-Identification model\" based on Generative Adversarial Networks (GAN) for detection and segmentation of DCIS ducts from multiplex immunohistochemistry (IHC) staining samples. We also trained a Spatially Constrained Convolutional Neural Network (SC-CNN) to detect and classify single cells based on their CA9 and FOXP3 expression. The DCIS-Identification model was evaluated on 8 whole slide images, resulting in an average Dice score of 0.95 for the segmentation performance. The single cell identification framework was tested on 10 randomly selected whole slide sections, achieving the average accuracy of 88.6% in a 5 fold cross validation scheme. With the proposed pipeline, we efficiently integrated deep learning, computational pathology and spatial statistics to report distinct differences in the microenvironments of DCIS and IDC/DCIS samples. The proposed pipeline provides a tool for a better understanding of the mechanism of tumours in DCIS and IDC/DCIS cases.","PeriodicalId":6827,"journal":{"name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","volume":"3 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78360315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1