Irene Pöllänen

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In this paper, we address the epidemiology and morphology questions of breast cancer with special focus on different cell features created by lesions. In addition, we provide an insight into feature extraction and classification schemes in the image analysis pipeline. Based on our conducted research work, a novel feature extraction approach, a modification(More)
In this paper, the performance of three Distance Transform on Curved Space-based features derived from digital H&E stained oncopathological images used in breast cancer pattern recognition scheme are compared. The three features utilized are SW-DTOCS, SW-WDTOCS and SW-3-4-DTOCS with three different sliding window (SW) sizes. The results imply that the(More)
In this paper, the current approaches and performance needs for whole slide image (WSI) analysis processing in breast cancer diagnostics are discussed. WSIs provide high resolution digital image data from the patient's diseased tissue. Digital whole slide images are typically very large and contain a high amount of information. Digitizing tissue specimen(More)
In this paper, cancerous nucleus is studied from the morphological point of view with focus on the analysis of anisonucleosis, nuclear deformity, hyperchromasia, and nucleocytoplasmic ratio with CAD-based (Computer Assisted Diagnosis) solutions. Mathematical Morphology (MM), more specifically Top-Hat Transform is used together with RGB color channel(More)
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