Deep Learning for Medical Image-Based Cancer Diagnosis

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...

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...

Heterogeneous data analysis: Online learning for medical-image-based diagnosis

Heterogeneous Data Analysis (HDA) is proposed to address a learning problem of medical image databases of Computed Tomographic Colonography (CTC). The databases are generated from clinical CTC images using a Computer-aided Detection (CAD) system, the goal of which is to aid radiologists' interpretation of CTC images by providing highly accurate, machine-based detection of colonic polyps. We aim...

Deep Learning and Computer-Aided Diagnosis for Medical Image Processing: A Personal Perspective

Deep Learning for Medical Image Processing: Overview, Challenges and Future

Healthcare sector is totally different from other industry. It is on high priority sector and people expect highest level of care and services regardless of cost. It did not achieve social expectation even though it consume huge percentage of budget. Mostly the interpretations of medical data is being done by medical expert. In terms of image interpretation by human expert, it is quite limited ...