Chapter 5: Cross color dominant deep autoencoder for quality enhancement of laparoscopic video: A hybrid deep learning and range-domain filtering-based approach
Apurba Dasa,b; S.S. Shylajaa a Department of CSE, PES University, Bangalore, Indiab Computer Vision (IoT), Tata Consultancy Services, Bangalore, India
Abstract
In minimally invasive surgery, laparoscopy video can be corrupted by haze, noise, oversaturated illumination, and other factors. These adverse internal environmental effects in turn impact the subsequent processing, such as segmentation, detection, and tracking the object or region of interest. Enhancement of each frame of video by considering color channels independently gives birth to unintended phantom colors due to ...
Get Machine Learning, Big Data, and IoT for Medical Informatics now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
