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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Vydané v:	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Ročník 9351; s. 383
Hlavní autori:	Su, Hai, Xing, Fuyong, Kong, Xiangfei, Xie, Yuanpu, Zhang, Shaoting, Yang, Lin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Germany 01.10.2015
Predmet:	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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