Explainable Deep Learning Models in Medical Image Analysis
نویسندگان
چکیده
منابع مشابه
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...
متن کاملExplainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models
With the availability of large databases and recent improvements in deep learning methodology, the performance of AI systems is reaching, or even exceeding, the human level on an increasing number of complex tasks. Impressive examples of this development can be found in domains such as image classification, sentiment analysis, speech understanding or strategic game playing. However, because of ...
متن کاملA 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,...
متن کاملVisual Analytics for Explainable Deep Learning
Recently, deep learning has been advancing the state of the art in artificial intelligence to a new level, and humans rely on artificial intelligence techniques more than ever. However, even with such unprecedented advancements, the lack of explanation regarding the decisions made by deep learning models and absence of control over their internal processes act as major drawbacks in critical dec...
متن کاملDeep 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...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Imaging
سال: 2020
ISSN: 2313-433X
DOI: 10.3390/jimaging6060052