Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification

Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification

The current study automatically identified regions of interest and classified breast tumors in whole slide images from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) using patch-based convolutional neural networks (CNNs). Pre-processing techniques were applied on whole slide images. T...

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Main Authors: Villareal, Rosiel Jazmine T, Abu, Patricia Angela R
Format: text
Published: Archīum Ateneo 2021
Subjects:
Computer vision
Convolutional neural networks
Breast cancer classification
Computer Sciences
Databases and Information Systems
Oncology
Online Access:https://archium.ateneo.edu/discs-faculty-pubs/248
https://link.springer.com/chapter/10.1007/978-3-030-90436-4_3
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Institution: Ateneo De Manila University
id ph-ateneo-arc.discs-faculty-pubs-1257
record_format eprints
spelling ph-ateneo-arc.discs-faculty-pubs-12572022-02-23T08:46:48Z Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification Villareal, Rosiel Jazmine T Abu, Patricia Angela R The current study automatically identified regions of interest and classified breast tumors in whole slide images from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) using patch-based convolutional neural networks (CNNs). Pre-processing techniques were applied on whole slide images. Then, whole slide images were tiled into patches, and patches containing regions of interest (ROIs) like nuclei-rich areas were identified. Afterwards, features from patches containing ROIs were extracted using CNNs and used to train patch-level classifiers. Finally, patch-level predictions were aggregated into slide-level predictions. Classification metrics like accuracy, precision, recall, and f1-score were used to evaluate results. 2021-01-01T08:00:00Z text https://archium.ateneo.edu/discs-faculty-pubs/248 https://link.springer.com/chapter/10.1007/978-3-030-90436-4_3 Department of Information Systems & Computer Science Faculty Publications Archīum Ateneo Computer vision Convolutional neural networks Breast cancer classification Computer Sciences Databases and Information Systems Oncology
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic Computer vision
Convolutional neural networks
Breast cancer classification
Computer Sciences
Databases and Information Systems
Oncology
spellingShingle Computer vision
Convolutional neural networks
Breast cancer classification
Computer Sciences
Databases and Information Systems
Oncology
Villareal, Rosiel Jazmine T
Abu, Patricia Angela R
Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification
description The current study automatically identified regions of interest and classified breast tumors in whole slide images from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) using patch-based convolutional neural networks (CNNs). Pre-processing techniques were applied on whole slide images. Then, whole slide images were tiled into patches, and patches containing regions of interest (ROIs) like nuclei-rich areas were identified. Afterwards, features from patches containing ROIs were extracted using CNNs and used to train patch-level classifiers. Finally, patch-level predictions were aggregated into slide-level predictions. Classification metrics like accuracy, precision, recall, and f1-score were used to evaluate results.
format text
author Villareal, Rosiel Jazmine T
Abu, Patricia Angela R
author_facet Villareal, Rosiel Jazmine T
Abu, Patricia Angela R
author_sort Villareal, Rosiel Jazmine T
title Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification
title_short Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification
title_full Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification
title_fullStr Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification
title_full_unstemmed Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification
title_sort patch-based convolutional neural networks for tcga-brca breast cancer classification
publisher Archīum Ateneo
publishDate 2021
url https://archium.ateneo.edu/discs-faculty-pubs/248
https://link.springer.com/chapter/10.1007/978-3-030-90436-4_3
_version_ 1726158608252534784

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