Shunmugam Mohan is a graduate student from the Department of Electrical Engineering. He joined the BMI imaging lab and started working with Dr.Gurcan from Winter 2008. His primary areas of research are Medical Image Processing, Signal Processing and Digital Communications. His Masters project was based on developing an ImageJ plugin for Haralick 3D texture analysis. He worked with Olcay Sertel on Content based Unsupervised Image Classification of Lymphoma images. He also worked with Jeff Prescott in the segmentation of MR images of patients with osteoarthritis. He has also developed websites for the CIALAB and the upcoming HIMA conference. He received his Bachelor of Engineering in Electronics and Communications Engineering from the Anna University, India.
The CIA lab has recently had 4 articles published in PLOS One and the Journal of Urology. Automated Staging Of T1 Bladder Cancer Using Digital Pathologic H&E Images: A Deep Learning approach (Journal of Urology). The paper discusses the need for accurately gauging tumor cell intrusion into Lamina Propria in an effort to substage bladder cancer. It explains how transfer learning in conjunction with Convolutional Neural Networks can be used to accurately identify different bladder layers and then compute the distance between tumor nuclei and Lamina Propria. The article is available here: https://www.jurology.com/article/S0022-5347(18)41148-2/pdf Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning (PLOS One). This paper examines a proposed methodology to automatically differentiate between NET and non-tumor regions based on images of Ki67 stained biopsies. It also uses transfer learning to exploit a rich set of features ...
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