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Convolutional Neural Network for Binary Classification of Chromophobe Renal Cell Carcinoma and Oncocytoma

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Abstract

Multiphoton microscopy images of chromophobe renal cell carcinoma and renal oncocytoma were classified using a convolutional neural network inspired by techniques in recent architectures and yielded over 70% accuracy.

© 2021 The Author(s)

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More Like This
Overview on convolutional neural network-based classification of red blood cells in lensless single random phase encoding

Timothy O’Connor, Christopher Hawxhurst, Leslie M. Shor, and Bahram Javidi
3W5A.3 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2021

Optical Reflectance Spectroscopy for Detection of Renal Cell Carcinoma Using Model-Driven Analysis

Aditya V. Mathker, Dheerendra Kashyap, Disha L. Peswani, Karim Bensalah, Wareef Kabbani, Altug Tuncel, Jeffrey Cadeddu, and Hanli Liu
BTuF43 Biomedical Optics (BIOMED) 2008

Fluorescence Spectroscopy: a noninvasive method for monitoring the treatment of metastatic renal cell carcinoma

Rodolfo Ferreira Marques, Marina de Souza Braga, Karen Cristina Barbosa Chaves, Camila Campanharo Barricheli, Cinthia Zanini Gomes, Lilia Coronato Courrol, and Maria Helena Bellini
PDPTuJ3 Latin America Optics and Photonics Conference (LAOP) 2010

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