Topology- and graph-informed imaging informatics : first International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. International Workshop on Topology- and Graph-Informed ...最新文献
Xiaoling Hu, Annabel Sorby-Adams, Frederik Barkhof, W Taylor Kimberly, Oula Puonti, Juan Eugenio Iglesias
{"title":"<i>P-Count</i>: Persistence-based Counting of White Matter Hyperintensities in Brain MRI.","authors":"Xiaoling Hu, Annabel Sorby-Adams, Frederik Barkhof, W Taylor Kimberly, Oula Puonti, Juan Eugenio Iglesias","doi":"10.1007/978-3-031-73967-5_10","DOIUrl":"https://doi.org/10.1007/978-3-031-73967-5_10","url":null,"abstract":"<p><p>White matter hyperintensities (WMH) are a hallmark of cerebrovascular disease and multiple sclerosis. Automated WMH segmentation methods enable quantitative analysis via estimation of total lesion load, spatial distribution of lesions, and number of lesions (i.e., number of connected components after thresholding), all of which are correlated with patient outcomes. While the two former measures can generally be estimated robustly, the number of lesions is highly sensitive to noise and segmentation mistakes - even when small connected components are eroded or disregarded. In this article, we present <i>P-Count</i>, an algebraic WMH counting tool based on persistent homology that accounts for the topological features of WM lesions in a robust manner. Using computational geometry, <i>P-Count</i> takes the persistence of connected components into consideration, effectively filtering out the noisy WMH positives, resulting in a more accurate count of true lesions. We validated <i>P-Count</i> on the ISBI2015 longitudinal lesion segmentation dataset, where it produces significantly more accurate results than direct thresholding.</p>","PeriodicalId":520840,"journal":{"name":"Topology- and graph-informed imaging informatics : first International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. International Workshop on Topology- and Graph-Informed ...","volume":"15239 ","pages":"100-110"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12372671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144987003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meiliong Xu, Nate Anderson, Richard M Levenson, Prateek Prasanna, Chao Chen
{"title":"A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging.","authors":"Meiliong Xu, Nate Anderson, Richard M Levenson, Prateek Prasanna, Chao Chen","doi":"10.1007/978-3-031-73967-5_12","DOIUrl":"10.1007/978-3-031-73967-5_12","url":null,"abstract":"<p><p>Fluorescence Imitating Brightfield Imaging (FIBI) represents an innovative approach in microscopy, providing real-time, non-destructive imaging of tissue without the need for the preparation of thin sections mounted on glass slides. The non-destructive nature of the technology permits tissue preservation for downstream analysis, which makes FIBI a promising alternative to traditional hematoxylin and eosin (H&E) staining in histopathology. Previous research has shown that FIBI can identify morphological features with similar or, in some cases, higher quality compared with H&E images. To comprehensively quantify the advantages and limitations of FIBI in tissue visualization, we propose a novel framework for characterizing the topological difference of FIBI and H&E slide pairs. Experiments are performed on slide pairs of FIBI and H&E imaging of the same tissue area. The proposed approach shows that FIBI can make morphological structures, like vessels, more salient and holds great promise as a complementary technique to H&E, offering novel insights into tissue architecture and potentially improving histopathological diagnostic accuracy.</p>","PeriodicalId":520840,"journal":{"name":"Topology- and graph-informed imaging informatics : first International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. International Workshop on Topology- and Graph-Informed ...","volume":"15239 ","pages":"122-133"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12094514/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144121747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}