Separation of benign and malignant glands in prostatic adenocarcinoma.
Med Image Comput Comput Assist Interv
; 16(Pt 3): 461-8, 2013.
Article
in En
| MEDLINE
| ID: mdl-24505794
This paper presents an analysis of the high resolution histopathology images of the prostate with a focus on the evolution of morphological gland features in prostatic adenocarcinoma. Here we propose a novel technique of labeling individual glands as malignant or benign. In the first step, the gland and nuclei objects of the images are automatically segmented. Individual gland units are segmented out by consolidating their lumina with the surrounding layers of epithelium and nuclei. The nuclei objects are segmented by using a marker controlled watershed algorithm. Two new features, Number of Nuclei Layer (N(NL)) and Ratio of Epithelial layer area to Lumen area (R(EL)) have been extracted from the segmented units. The main advantage of this approach is that it can detect individual malignant gland units, irrespective of neighboring histology and/or the spatial extent of the cancer. The proposed algorithm has been tested on 40 histopathology scenes taken from 10 high resolution whole mount images and achieved a sensitivity of 0.83 and specificity of 0.81 in a leave-75%-out cross-validation.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Prostatic Neoplasms
/
Pattern Recognition, Automated
/
Adenocarcinoma
/
Cell Nucleus
/
Subtraction Technique
/
Support Vector Machine
/
Microscopy
Type of study:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
/
Male
Language:
En
Journal:
Med Image Comput Comput Assist Interv
Journal subject:
DIAGNOSTICO POR IMAGEM
/
INFORMATICA MEDICA
Year:
2013
Document type:
Article
Affiliation country:
Country of publication: