Literature DB >> 10066352

Similarity measurement method for the classification of architecturally differentiated images.

Y Smith1, G Zajicek, M Werman, G Pizov, Y Sherman.   

Abstract

A similarity measurement method for the classification of architecturally differentiated image sections is described. The strength of the method is demonstrated by performing the complex task of assigning severity grading (Gleason grading) to histological slides of prostate cancer. As shown, all that is required to employ the method is a small set of preclassified images. The images can be real world images acquired by means of a camera, computer tomography, etc., or schematic drawings representing samples of different classes. The schematic option allows a quick test of the method for a particular classification problem. Copyright 1999 Academic Press.

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Mesh:

Year:  1999        PMID: 10066352     DOI: 10.1006/cbmr.1998.1500

Source DB:  PubMed          Journal:  Comput Biomed Res        ISSN: 0010-4809


  8 in total

1.  Automated prostate tissue referencing for cancer detection and diagnosis.

Authors:  Jin Tae Kwak; Stephen M Hewitt; André Alexander Kajdacsy-Balla; Saurabh Sinha; Rohit Bhargava
Journal:  BMC Bioinformatics       Date:  2016-06-01       Impact factor: 3.169

2.  Multiview boosting digital pathology analysis of prostate cancer.

Authors:  Jin Tae Kwak; Stephen M Hewitt
Journal:  Comput Methods Programs Biomed       Date:  2017-02-22       Impact factor: 5.428

3.  High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models.

Authors:  James P Monaco; John E Tomaszewski; Michael D Feldman; Ian Hagemann; Mehdi Moradi; Parvin Mousavi; Alexander Boag; Chris Davidson; Purang Abolmaesumi; Anant Madabhushi
Journal:  Med Image Anal       Date:  2010-04-29       Impact factor: 8.545

4.  Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images.

Authors:  Wenyuan Li; Jiayun Li; Karthik V Sarma; King Chung Ho; Shiwen Shen; Beatrice S Knudsen; Arkadiusz Gertych; Corey W Arnold
Journal:  IEEE Trans Med Imaging       Date:  2018-10-12       Impact factor: 10.048

5.  Extraction of prostatic lumina and automated recognition for prostatic calculus image using PCA-SVM.

Authors:  Zhuocai Wang; Xiangmin Xu; Xiaojun Ding; Hui Xiao; Yusheng Huang; Jian Liu; Xiaofen Xing; Hua Wang; D Joshua Liao
Journal:  Comput Math Methods Med       Date:  2011-02-24       Impact factor: 2.238

6.  Computer-aided identification of prostatic adenocarcinoma: Segmentation of glandular structures.

Authors:  Yahui Peng; Yulei Jiang; Laurie Eisengart; Mark A Healy; Francis H Straus; Ximing J Yang
Journal:  J Pathol Inform       Date:  2011-07-26

7.  Multimodal microscopy for automated histologic analysis of prostate cancer.

Authors:  Jin Tae Kwak; Stephen M Hewitt; Saurabh Sinha; Rohit Bhargava
Journal:  BMC Cancer       Date:  2011-02-09       Impact factor: 4.430

8.  Automated image based prominent nucleoli detection.

Authors:  Choon K Yap; Emarene M Kalaw; Malay Singh; Kian T Chong; Danilo M Giron; Chao-Hui Huang; Li Cheng; Yan N Law; Hwee Kuan Lee
Journal:  J Pathol Inform       Date:  2015-06-23
  8 in total

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