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20192022
most citedHistopathologic Image Processing: A Review

24 citations · 27 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV20221 cited

Multiscale Analysis for Improving Texture Classification

Steve T. M. Ataky, Diego Saqui, Jonathan de Matos +2

Information from an image occurs over multiple and distinct spatial scales. Image pyramid multiresolution representations are a useful data structure for image analysis and manipul…

cs.CV2021

Machine Learning Methods for Histopathological Image Analysis: A Review

Jonathan de Matos, Steve Tsham Mpinda Ataky, Alceu de Souza Britto +2

Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis. The analysis of such images is not only time and resource consuming,…

cs.CV2019

Texture CNN for Histopathological Image Classification

Jonathan de Matos, Alceu de S. Britto, Luiz E. S. de Oliveira +1

Biopsies are the gold standard for breast cancer diagnosis. This task can be improved by the use of Computer Aided Diagnosis (CAD) systems, reducing the time of diagnosis and reduc…

cs.CV201924 cited

Histopathologic Image Processing: A Review

Jonathan de Matos, Alceu de Souza Britto, Luiz E. S. Oliveira +1

Histopathologic Images (HI) are the gold standard for evaluation of some tumors. However, the analysis of such images is challenging even for experienced pathologists, resulting in…

cs.CV2019

Double Transfer Learning for Breast Cancer Histopathologic Image Classification

Jonathan de Matos, Alceu de S. Britto, Luiz E. S. Oliveira +1

This work proposes a classification approach for breast cancer histopathologic images (HI) that uses transfer learning to extract features from HI using an Inception-v3 CNN pre-tra…