Deep Learning for Medical Image Analysis

TL;DR

This paper reviews novel deep learning methods for analyzing medical images, focusing on brain abnormality detection, recognition, and segmentation, and discusses the author's Ph.D. research plans.

Contribution

It introduces new end-to-end trainable deep learning approaches specifically designed for medical image analysis tasks.

Findings

Effective brain abnormality detection methods

Improved recognition accuracy

Enhanced segmentation techniques

Abstract

This report describes my research activities in the Hasso Plattner Institute and summarizes my Ph.D. plan and several novels, end-to-end trainable approaches for analyzing medical images using deep learning algorithm. In this report, as an example, we explore different novel methods based on deep learning for brain abnormality detection, recognition, and segmentation. This report prepared for the doctoral consortium in the AIME-2017 conference.