Detection of follicles from IHC-stained slides of follicular lymphoma using iterative watershed.

IEEE Transactions on Bio-medical Engineering
Siddharth SamsiMetin Gurcan

Abstract

Follicular lymphoma (FL) is one of the most common types of nonHodgkin lymphoma in the U.S. Diagnosis of FL is based on tissue biopsy that shows characteristic morphologic and immunohistochemical (IHC) findings. Our group's work focuses on the development of computer-aided image-analysis techniques to improve the FL grading. Since centroblast enumeration needs to be performed in malignant follicles, the development of an automated system to accurately identify follicles on digital images of lymphoid tissue is an important step. In this letter, we describe an automated system to identify follicles in IHC-stained tissue sections. A unique feature of the system described here is the use of texture and color information to mimic the process that a human expert might use to identify follicle regions. Comparison of system-generated results with expert-generated ground truth has shown promising results with a mean similarity score of 87.11%.

References

Jan 1, 1994·IEEE Transactions on Medical Imaging·A P ZijdenbosA C Palmer
Mar 11, 2009·IEEE Transactions on Bio-medical Engineering·Jierong Cheng, Jagath C Rajapakse

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Citations

Jan 7, 2014·Journal of Pathology Informatics·Gerard LozanskiMetin N Gurcan
Jan 27, 2012·Journal of the American Medical Informatics Association : JAMIA·Lee A D CooperJoel H Saltz
Dec 31, 2015·BMC Medical Informatics and Decision Making·Mohammad Faizal Ahmad FauziMetin N Gurcan
Jan 1, 2014·Cytometry. Part a : the Journal of the International Society for Analytical Cytology·Evgenios N KornaropoulosMetin N Gurcan
Aug 10, 2015·Journal of Neuro-oncology·Mohammad Faizal Ahmad FauziMetin N Gurcan
Dec 4, 2019·International Journal of Oncology·Zunmin ZhuWeihong Ren
Jan 15, 2019·JCO Clinical Cancer Informatics·Jacob JordanLee A D Cooper

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