2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)最新文献_第6页

Hybrid deep autoencoder with Curvature Gaussian for detection of various types of cells in bone marrow trephine biopsy images 具有高斯曲率的混合深度自编码器用于骨髓环钻活检图像中不同类型细胞的检测

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950694

Tzu-Hsi Song, Victor Sanchez, Hesham EIDaly, N. Rajpoot

引用次数: 20

Self supervised deep representation learning for fine-grained body part recognition 用于细粒度身体部位识别的自监督深度表示学习

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950587

Pengyue Zhang, Fusheng Wang, Yefeng Zheng

{"title":"Self supervised deep representation learning for fine-grained body part recognition","authors":"Pengyue Zhang, Fusheng Wang, Yefeng Zheng","doi":"10.1109/ISBI.2017.7950587","DOIUrl":"https://doi.org/10.1109/ISBI.2017.7950587","url":null,"abstract":"Difficulty on collecting annotated medical images leads to lack of enough supervision and makes discrimination tasks challenging. However, raw data, e.g., spatial context information from 3D CT images, even without annotation, may contain rich useful information. In this paper, we exploit spatial context information as a source of supervision to solve discrimination tasks for fine-grained body part recognition with conventional 3D CT and MR volumes. The proposed pipeline consists of two steps: 1) pre-train a convolutional network for an auxiliary task of 2D slices ordering in a self-supervised manner; 2) transfer and fine-tune the pre-trained network for fine-grained body part recognition. Without any use of human annotation in the first stage, the pre-trained network can still outperform CNN trained from scratch on CT as well as M-R data. Moreover, by comparing with pre-trained CNN from ImageNet, we discover that the distance between source and target tasks plays a crucial role in transfer learning. Our experiments demonstrate that our approach can achieve high accuracy with a slice location estimation error of only a few slices on CT and MR data. To the best of our knowledge, our work is the first attempt studying the problem of robust body part recognition at a continuous level.","PeriodicalId":6547,"journal":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88597039","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: 47

An algorithm for fully automatic detection of calcium in chest CT imaging 胸部CT影像中钙的全自动检测算法

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950516

Hui Tang, Mehdi Moradi, Prasanth Prasanna, Hongzhi Wang, T. Syeda-Mahmood

{"title":"An algorithm for fully automatic detection of calcium in chest CT imaging","authors":"Hui Tang, Mehdi Moradi, Prasanth Prasanna, Hongzhi Wang, T. Syeda-Mahmood","doi":"10.1109/ISBI.2017.7950516","DOIUrl":"https://doi.org/10.1109/ISBI.2017.7950516","url":null,"abstract":"Detection of calcified plaques in coronary arteries is helpful in cardiovascular disease risk assessment. This is often performed by radiologists on computed tomography (CT) images. We work towards an automatic solution for calcium detection in CT images. Most of previous work in this area combines CT and CTA for this purpose to facilitate the localization of the coronary arteries. Given the cost and dose advantages of using only CT scan compared to using both CT and CTA, we propose a solution for automatic calcium assessment in CT. We model the whole chest including all heart chambers and main arteries. Instead of localizing calcium candidates with respect to the coronary artery alone, we assess their position with respect to eight other anatomies, segmented from CT images using joint atlas label fusion methodology. This comprehensive spatial information together with other types of features such as shape, size and texture of each calcium candidate is used with a random forest classifier trained on 104 patients to detect coronary calcification. The results show that our method has a precision of 95.1% and a recall of 89.0% in classifying calcium candidates found based on thresholding. In the patient level, using this method, all the test patients with true calcification were detected as positive, yielding a patient level sensitivity of 100%. Among the test patients without calcification, 44 out of 56 patients resulted in no calcium finding, yielding a patient level specificity of 78.6%. We quantified the whole heart Agatston score for the manual and the automatically detected calcium on the 22 diseased test cases, and found a Pearson correlation coefficient of 0.98. These results show that our proposed framework can reliably detect calcification using CT data.","PeriodicalId":6547,"journal":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89343344","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

Longitudinal analysis of diffusion-weighted MRI with a ball-and-sticks model 球棒模型对弥散加权MRI的纵向分析

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950635

G. Arkesteijn, D. Poot, M. Niestijl, M. Vernooij, W. Niessen, L. Vliet, F. Vos

引用次数: 1

Brain MRI super-resolution using deep 3D convolutional networks 使用深度3D卷积网络的脑MRI超分辨率

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950500

Chi-Hieu Pham, Aurélien Ducournau, Ronan Fablet, F. Rousseau

引用次数: 193

Classifying histopathology whole-slides using fusion of decisions from deep convolutional network on a collection of random multi-views at multi-magnification 利用深度卷积网络在随机多视图集合上的决策融合对组织病理学全片进行分类

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950690

Kausik Das, S. Karri, Abhijit Guha Roy, J. Chatterjee, D. Sheet

{"title":"Classifying histopathology whole-slides using fusion of decisions from deep convolutional network on a collection of random multi-views at multi-magnification","authors":"Kausik Das, S. Karri, Abhijit Guha Roy, J. Chatterjee, D. Sheet","doi":"10.1109/ISBI.2017.7950690","DOIUrl":"https://doi.org/10.1109/ISBI.2017.7950690","url":null,"abstract":"Histopathology forms the gold standard for confirmed diagnosis of a suspicious hyperplasia being benign or malignant and for its sub-typing. While techniques like whole-slide imaging have enabled computer assisted analysis for exhaustive reporting of the tissue section, it has also given rise to the big-data deluge and the time complexity associated with processing GBs of image data acquired over multiple magnifications. Since preliminary screening of a slide into benign or malignant carried out on the fly during the digitization process can reduce a Pathologist's work load, to devote more time for detailed analysis, slide screening has to be performed on the fly with high sensitivity. We propose a deep convolutional neural network (CNN) based solution, where we analyse images from random number of regions of the tissue section at multiple magnifications without any necessity of view correspondence across magnifications. Further a majority voting based approach is used for slide level diagnosis, i.e., the class posteriori estimate of each views at a particular magnification is obtained from the magnification specific CNN, and subsequently posteriori estimate across random multi-views at multi-magnification are voting filtered to provide a slide level diagnosis. We have experimentally evaluated performance using a patient level 5-folded cross-validation with 58 malignant and 24 benign cases of breast tumors to obtain average accuracy of 94.67 ± 14.60%, sensitivity of 96.00 ± 8.94%, specificity of 92.00 ± 17.85% and F-score of 96.24 ± 5.29% while processing each view in ≈ 10 ms.","PeriodicalId":6547,"journal":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86859980","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: 44

Longitudinal multi-scale mapping of infant cortical folding using spherical wavelets 基于球面小波的婴儿皮层折叠纵向多尺度映射

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950476

Dingna Duan, I. Rekik, Shun-ren Xia, Weili Lin, J. Gilmore, D. Shen, Gang Li

{"title":"Longitudinal multi-scale mapping of infant cortical folding using spherical wavelets","authors":"Dingna Duan, I. Rekik, Shun-ren Xia, Weili Lin, J. Gilmore, D. Shen, Gang Li","doi":"10.1109/ISBI.2017.7950476","DOIUrl":"https://doi.org/10.1109/ISBI.2017.7950476","url":null,"abstract":"The dynamic development of brain cognition and motor functions during infancy are highly associated with the rapid changes of the convoluted cortical folding. However, little is known about how the cortical folding, which can be characterized on different scales, develops in the first two postnatal years. In this paper, we propose a curvature-based multi-scale method using spherical wavelets to map the complicated longitudinal changes of cortical folding during infancy. Specifically, we first decompose the cortical curvature map, which encodes the cortical folding information, into multiple spatial-frequency scales, and then measure the scale-specific wavelet power at 6 different scales as quantitative indices of cortical folding degree. We apply this method on 219 longitudinal MR images from 73 healthy infants at 0, 1, and 2 years of age. We reveal that the changing patterns of cortical folding are both scale-specific and region-specific. Particularly, at coarser spatial-frequency levels, the majority of the primary folds flatten out, while at finer spatial-frequency levels, the majority of the minor folds become more convoluted. This study provides valuable insights into the longitudinal changes of infant cortical folding.","PeriodicalId":6547,"journal":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75782398","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: 3

An efficient estimation algorithm for the calibration of low-cost SS-OCT systems 一种用于低成本SS-OCT系统标定的有效估计算法

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950724

A. T. Zavareh, O. Barajas, S. Hoyos

引用次数: 8

Automatic segmentation of fetal brain using diffusion-weighted imaging cues 利用弥散加权成像线索对胎儿大脑进行自动分割

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950640

R. Shishegar, Anand A. Joshi, M. Tolcos, D. Walker, L. Johnston

引用次数: 3

Spatio-temporally regularized 4-D cardiovascular C-arm CT reconstruction using a proximal algorithm 使用近端算法的时空正则化4d心血管c臂CT重建

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Pub Date : 2017-04-18 DOI: 10.1109/ISBI.2017.7950466

O. Taubmann, M. Unberath, G. Lauritsch, S. Achenbach, A. Maier

引用次数: 5