DeepLearning CAD 2018 : Deep Learning for Computer-Aided Diagnosis (CAD) systems- IPAS 2018- Special Session
|Link: http://Deep learning for Computer-Aided Diagnosis (CAD) systems|
Call For Papers
Call for Special Session Papers
Deep learning for Computer-Aided Diagnosis (CAD) systems
Mr. Ramzi GUETARI, ISI, Tunis El Manar University, Mme. Nawres KHLIFA, ISTMT, Tunis El Manar University
Third IEEE International Conference on Image Processing, Applications and Systems (IPAS 2018)
12-14 December 2018, University of Nice Sophia Antipolis, France
Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging. It enables early disease detection and robust diagnosis decision. CAD systems are more and more developed in order to help and improve the diagnosis, to overcome the limits of the human analysis, and to detect the pathological changes which cannot be sometimes detected by doctors.
CAD systems require the extraction of the most significant features to recognize or classify data. However, feature extraction is a difficult and boring task. Deep learning based systems overcome this limitation by extracting automatically relevant features. Indeed, it allows using directly the whole image and avoids the search for the best representation. Importantly, a deep learning process can learn which features to optimally place in which level on its own.
This special session is focused on the application of deep learning methods in medical images analysis and CAD systems development.
The aim of this special session is to attract researchers interested in CAD development using deep learning. Both theoretical and application contributions will be entertained.
Paper Submission September 11, 2018
Notification of acceptance October 15, 2018
Final Decision October 30, 2018
The session will seek original work on the following aspects but not limited to:
· Deep learning for:
- Tumor cell analysis
- Deformation detection
- Tissue Image Classification
- Texture Analysis
- Nodule classification
More information about the Conference including details on the submission process and authors kit is available at http://ipas.ieee.tn