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Software . 2022

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Software . 2022

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Multi-lens Neural Machine (MLNM)

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 06 Feb 2022Publisher:Zenodo

Authors: Oner, Mustafa Umit; Ng, Mei Ying;

doi: 10.5281/zenodo.5982398

Multi-lens Neural Machine (MLNM)

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Abstract

This repository is the official implementation of the paper: An AI-assisted Tool For Efficient Prostate Cancer Diagnosis. It uses the data: Digital Pathology Dataset for Prostate Cancer Diagnosis. We developed a multi-lens (or multi-resolution) deep learning pipeline detecting malignant glands in core needle biopsies of low-grade prostate cancer to assist pathologists in diagnosis. The pipeline consisted of two stages: the gland segmentation model detected the glands within the sections and the multi-lens model classified each detected gland into benign vs. malignant. The multi-lens model exploited both morphology information (of nuclei and glands from high resolution images - 40× and 20×) and neighborhood information (for architectural patterns from low resolution images - 10× and 5×), important in prostate gland classification.

This study was funded by the Biomedical Research Council of the Agency for Science, Technology and Research, Singapore.

Related Organizations

Agency for Science, Technology and Research
Singapore
Bioinformatics Institute
Singapore

Keywords

Machine Learning, Deep Learning, Artificial Intelligence, Prostate Cancer, Digital Pathology, Histopathology, Whole Slide Image Analysis, Computational Pathology

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