Functional Assessment of Synoptic Pathology Reporting for Ovarian Cancer.

Background: Ovarian cancer has one of the highest death/incidence rates and is commonly diagnosed at an advanced stage. In the recent WHO classification, new histotypes were classified which respond differently to chemotherapy. The e-standardized synoptic cancer pathology reports offer the clinicians essential and reliable information.

Hot-spot selection and evaluation methods for whole slice images of meningiomas and oligodendrogliomas.

The paper presents a combined method for an automatic hot-spot areas selection based on penalty factor in the whole slide images to support the pathomorphological diagnostic procedure. The studied slides represent the meningiomas and oligodendrogliomas tumor on the basis of the Ki-67/MIB-1 immunohistochemical reaction. It allows determining the tumor proliferation index as well as gives an indication to the medical treatment and prognosis.

Comparison of the manual, semiautomatic, and automatic selection and leveling of hot spots in whole slide images for Ki-67 quantification in meningiomas.

Background. This paper presents the study concerning hot-spot selection in the assessment of whole slide images of tissue sections collected from meningioma patients. The samples were immunohistochemically stained to determine the Ki-67/MIB-1 proliferation index used for prognosis and treatment planning.

Computer approach to recognition of Fuhrman grade of cells in clear-cell renal cell carcinoma.

Objective: To present a computerized system for recognition of Fuhrman grade of cells in clear-cell renal cell carcinoma on the basis of microscopic images of the neoplasm cells in application of hematoxylin and eosin staining.

Study Design: The applied methods use combined gradient and mathematical morphology to obtain nuclei and classifiers in the form of support vector machine to estimate their Fuhrman grade. The starting point is a microscopic kidney image, which is subject to the advanced methods of preprocessing, leading finally to estimation of Fuhrman grade of cells and the whole analyzed image.

Nucleolus detection in the Fuhrman grading system for application in CCRC.

The paper presents a method for nucleolus detection in images of nuclei in clear-cell renal carcinoma (CCRC). The method is based on the similarity of the nuclei image and the two-dimensional paraboloidal window function. The results of numerical experiments performed on almost 2600 images of CCRC nuclei have confirmed the good accuracy of the method.