Deep Learning in Medical Image Analysis

Deep Learning for Medical Image Analysis

This report describes my research activities in the Hasso Plattner Institute and summarizes my PhD plan and several novel, endto-end trainable approches for analyze medical images using deep learning algorithm. In this report, as an example, we explore diffrent novel methods based on deep learning for brain abnormality detection, recognition and segmentation. This report prepared for doctoral c...

A survey on deep learning in medical image analysis

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection,...

Deep Learning for Medical Image Segmentation

This report provides an overview of the current state of the art deep learning architectures and optimisation techniques, and uses the ADNI hippocampus MRI dataset as an example to compare the effectiveness and efficiency of different convolutional architectures on the task of patch-based 3dimensional hippocampal segmentation, which is important in the diagnosis of Alzheimer’s Disease. We found...

Machine Learning Applications in Medical Image Analysis

Deep Learning for Biomedical Texture Image Analysis

This paper shows promising results in the application of Convolutional Neural Networks (CNN) to biomedical imaging. Texture is often dominant in biomedical imaging and its analysis is essential to automatically obtain meaningful information. Therefore, we introduce a method using a Texture CNN for the classification of biomedical images. We test our approach on three datasets of liver tissues i...