Cascaded-Automatic Segmentation for Schistosoma japonicum eggs in images of fecal samples-Reference-Cited by-同舟云学术

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Cascaded-Automatic Segmentation for Schistosoma japonicum eggs in images of fecal samples

Published:2014-09 Issue: Volume:52 Page:18-27
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Zhang Junjie,Lin Yunyu,Liu Yan,Li Zhengyu,Li Zhong,Hu Shan,Liu Zhiyuan,Lin Dandan,Wu Zhongdao

Funder

Chinese Important Scientific Research Project on Infectious Diseases

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference37 articles.

1. Automatic identification of human Helminth eggs on microscopic fecal specimens using digital image processing and an artificial neural network;Yang;IEEE Trans. Biomed. Eng.,2001

2. An expert diagnosis system for classification of human parasite eggs based on multi-class SVM;Avci;Expert Syst. Appl.,2009

3. A robust technique based on invariant moments – ANFIS for recognition of human parasite eggs in microscopic images;Dogantekin;Expert Syst. Appl.,2008

4. Biological shape characterization for automatic image recognition and diagnosis of protozoan parasites of the genus eimeria;Castañón;Pattern Recognit.,2007

5. Using active learning to annotate microscope images of parasite eggs;Nugent;Artif. Intell.,2006

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1. Segmentation Approaches of Parasite Eggs in Microscopic Images: A Survey;SN Computer Science;2024-04-06

2. Research Progress in the Early Warning of Chicken Diseases by Monitoring Clinical Symptoms;Applied Sciences;2022-05-31

3. Development of New Staining Procedures for Diagnosing Cryptosporidium spp. in Fecal Samples by Computerized Image Analysis;Microscopy and Microanalysis;2021-10-15

4. FecalNet: Automated detection of visible components in human feces using deep learning;Medical Physics;2020-07-18

5. Mathematical algorithm for the automatic recognition of intestinal parasites;PLOS ONE;2017-04-14

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