Blood vessel characterization using virtual 3D models and convolutional neural networks in fluorescence microscopy

Aritra Chowdhury, Dmitry V. Dylov, Qing Li, Michael Macdonald, Dan E. Meyer, Michael Marino, Alberto Santamaria-Pang

Результат исследований: Глава в книге, отчете, сборнике статейМатериалы для конференциирецензирование

5 Цитирования (Scopus)

Аннотация

We report an automated method for characterization of microvessel morphology in micrographs of brain tissue sections to enable the facile, quantitative analysis of vascular differences across large datasets consisting of hundreds of images with thousands of blood vessel objects. Our objective is to show that virtual 3D parametric models of vasculature are adequately capable of representing the morphology of naturally acquired data in neuropathology. In this work, we focus on three distinct morphologies that are most frequently observed in formalin-fixed, paraffin-embedded (FFPE) human brain tissue samples: single blood vessels showing no (or collapsed) significant lumen ('RoundLumen-'); single blood vessels with distinct lumen ('RoundLumen+'); two blood vessels bundled together in close proximity ('Twins'). The analysis involves extraction of features using pre-trained convolutional neural networks. A hierarchical classification is performed to distinguish single blood vessels (RoundLumen) from Twins; followed by a more granular classification between RoundLumen- and RoundLumen+. A side-by-side comparison of the virtual and natural data models is presented. We observed that classification models built on the virtual data perform well achieving accuracies of 92.8% and 98.3% for the two aforementioned classification tasks respectively.

Язык оригиналаАнглийский
Название основной публикации2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017
ИздательIEEE Computer Society
Страницы629-632
Число страниц4
ISBN (электронное издание)9781509011711
DOI
СостояниеОпубликовано - 15 июн. 2017
Опубликовано для внешнего пользованияДа
Событие14th IEEE International Symposium on Biomedical Imaging, ISBI 2017 - Melbourne, Австралия
Продолжительность: 18 апр. 201721 апр. 2017

Серия публикаций

НазваниеProceedings - International Symposium on Biomedical Imaging
ISSN (печатное издание)1945-7928
ISSN (электронное издание)1945-8452

Конференция

Конференция14th IEEE International Symposium on Biomedical Imaging, ISBI 2017
Страна/TерриторияАвстралия
ГородMelbourne
Период18/04/1721/04/17

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