A general framework for the segmentation of follicular lymphoma virtual slides

Abstract Follicular lymphoma (FL) is one of the most common types of non-Hodgkin's lmphomas in the world. Diagnosis of FL is based on morphological and immunohistochemical characteristics found on tissue sections. Our project's aim is to develop computer-aided analysis tools on virtual sli...

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Veröffentlicht in:	Computerized medical imaging and graphics 2012-09, Vol.36 (6), p.442-451
Hauptverfasser:	Oger, Myriam, Belhomme, Philippe, Gurcan, Metin N
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Biopsy - methods Follicular lymphoma Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Immunohistochemistry Internal Medicine Lymphoma, Follicular - pathology Microscopy - methods Other Pattern Recognition, Automated - methods Quality control Registration Reproducibility of Results Sensitivity and Specificity User-Computer Interface Virtual slide
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Beschreibung
Zusammenfassung:	Abstract Follicular lymphoma (FL) is one of the most common types of non-Hodgkin's lmphomas in the world. Diagnosis of FL is based on morphological and immunohistochemical characteristics found on tissue sections. Our project's aim is to develop computer-aided analysis tools on virtual slide images (VSI) of lymphoid tissues with the purpose of improving the FL grading performed in malignant follicles. In this paper, we focus on the first step of our work, an automated system for detecting follicles in VSI of lymphoid tissues. To mimic the human expert process, the system works on low-resolution CD20 images and maps the follicle boundaries on high-resolution H&E images.
ISSN:	0895-6111 1879-0771
DOI:	10.1016/j.compmedimag.2012.05.003