DCNN based Oral Cancer Screening using Whole Slide Cytology Images : Effect of Increased Patch Size

• Cases of Oral Cancer are increasing around the world. Oral Squamous Cell Carcinomas constitute majority of all Oral Cancer cases and arise from the oral epithelium. Although this type of Oral Cancer is highly accessible to clinicians as they are superficial, they are often discovered late. To improve early detection in order to increase the chances of survival, we propose a Deep Convolutional Neural Network based framework on whole slide cytology images. In this ongoing work, we have shown that increasing the size of the patch centered at the detected nuclei, increases the accuracy of classification of the pathological condition of the nuclei using only slide-level labels.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Medical Engineering -- Medical Image Processing (hsv//eng)

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

Nyckelord

Computerized Image Processing

Datoriserad bildbehandling

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