Robust Cell Detection and Segmentation in Histopathological Images Using Sparse Reconstruction and Stacked Denoising Autoencoders

Computer-aided diagnosis (CAD) is a promising tool for accurate and consistent diagnosis and prognosis. Cell detection and segmentation are essential steps for CAD. These tasks are challenging due to variations in cell shapes, touching cells, and cluttered background. In this paper, we present a cel...

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Bibliographic Details

Published in:	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Vol. 9351; p. 383
Main Authors:	Su, Hai, Xing, Fuyong, Kong, Xiangfei, Xie, Yuanpu, Zhang, Shaoting, Yang, Lin
Format:	Journal Article
Language:	English
Published:	Germany 01.10.2015
Subjects:	Algorithms Brain Neoplasms - pathology Cell Count Cell Shape Diagnosis, Computer-Assisted - methods Humans Image Processing, Computer-Assisted Lung Neoplasms - pathology Machine Learning Reproducibility of Results Sensitivity and Specificity
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