AI in Cancer Pathology | IEEE BUBT STUDENT BRANCH
Channel: IEEE BUBT Student Branch
Date: 2021-08-06

On  6th August, 2021, IEEE BUBT Student Branch and BUBT ICSCT organized an event about “AI in Cancer Pathology”.
The speaker of the event, Dr. Sabeena Beevi K received a Ph.D. degree from the University of Kerala in 2018 and an M.Tech. Degree in computer science with a specialization in Digital Image Computing from the Computer Science Department of Kerala University. She has been working as Associate Professor, Electrical and Electronics Engineering, Dpt. of T K M College of Engineering Kollam for the last 23 years. Her research interests include pattern recognition, machine learning, medical image analysis, and computer vision. She has participated in the MITOS-ATYPIA 2014 Grand Challenge and won third place for one data set. Received Best Thesis Award 2019 from IEEE Communication Society through ‘GATE’7’ contest. Bagged Guidance Award for the Best Project from 5th National Level IEEE Project Competition-2021. She is an active IEEE and CSI member from the Kerala section. She is carrying out consultancy and sponsored projects with RCC Trivandrum and Power Grid Corporation of India P(Ltd).

The main reason to organize the webinar is to introduce the topic “Artificial Intelligence in Cancer Pathology.” The theme of the session is research and innovation for woman empowerment. The speech was based on artificial intelligence. The speaker started with the difference between AI, ML and DL and how these are related to each other. Then she showed a chart related to mortality rate due to various cancers. She talked about Sputum cytology analysis techniques and how a simple microscopy modification relevant on an engineering baisi can be done so as to make it compatible with sputum cytology and save human lives. She introduced Fourier Ptychography Microscopy (FPM), which offers a simple computational technique that provides high resolution images and is capable of providing mechanical scanning. She also talked about the Adafruit 32x32 RGB LED Matrix Panel and its advantages, implementation setup, Result-FPM, Result-Detection of it, Architecture evaluation, and future scopes. In the future scope section, she talked about the Nottingham Grading System, different appearances of mitotic cells, Whole Slide Images (WSI), Mitosis detection, segmentation, color space transformation, and the Multi Classifier System (MCS) and many more. The question answer session of the workshop also went smoothly. The speaker was very interested in the questions and answered them thoroughly. Through this virtual webinar, the participants got a chance to know about the topic briefly and why it is important and how we can use it for future aspects. And get a chance to know about Cancer Pathology, which has been an active research field.

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