Melanoma Cell Detection in Lymph Nodes Histopathological Images using Deep Learning

Salah Alheejawi
2020 Zenodo  
Histopathological images are widely used to diagnose diseases including skin cancer. As digital histopathological images are typically of very large size, in the order of several billion pixels, automated identification of all abnormal cell nuclei and their distribution within multiple tissue sections would assist rapid comprehensive diagnostic assessment. In this paper, we propose a technique, using deep learning algorithms, to segment the cell nuclei in Hematoxylin and Eosin (H&E) stained
more » ... n (H&E) stained images and detect the abnormal melanocytes within histopathological images. The Nuclear segmentation is done by using a Convolutional Neural Network (CNN) and hand-crafted features are extracted for each nucleus. The segmented nuclei are then classified into normal and abnormal nuclei using a Support Vector Machine classifier. Experimental results show that the CNN can segment the nuclei with more than 90% accuracy. The proposed technique has a low computational complexity.
doi:10.5281/zenodo.4032376 fatcat:jelb5y6gjjgtvdvxdbl67u57jy