Computer Vision and Image Processing for Computer-Aided Diagnosis

Call for Papers

Computer-aided diagnosis (CAD) can be defined as all the computer-based tools that assist medical doctors either for diagnosis or to guide medical intervention. Modern computer vision/image processing techniques are allowing CAD technologies to spread in many medical/biomedical areas and are becoming an indispensable tool for modern medicine imaging systems.

CAD can be applied to all sorts of imaging data, which may come from modalities such as MRI, PET, ultrasounds, X-rays, and microscopy images. Novel computer vision/image processing methods are allowing numerous breakthroughs for early diagnosis and image guided therapy with substantial benefits for patients' health and costs saving for patient care providers. Examples are the algorithms for automatic detection and visualization of lesions, tumors, structures, and anatomy which have seen wide adoption in radiology clinics.In this special issue, we aim at bringing together high quality research in CAD which employs medical image analysis approaches developed by researchers in computer vision/image processing and medical imaging fields to advance this interdisciplinary field. Areas of interest in this special issue are all aspects of image processing research for biomedical/medical image analysis whose final aim is to assist doctors in providing a medical diagnosis. Potential topics include, but are not limited to:

• Computer-aided detection/diagnosis of lesions (e.g., lung cancer, breast cancer, colon cancer, liver cancer, acute disease, chronic disease, osteoporosis, and diabetic retinopathy)
• Medical image analysis (e.g., pattern recognition, classification, and segmentation) of lesions, lesion stage, organs, anatomy, status of disease, and medical data
• Multimodality data fusion (e.g., PET/CT, projection X-ray/CT, X-ray/ultrasound) for medical imaging diagnosis

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/ijbi/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/ijbi/cvip/ according to the following timetable:

Lead Guest Editor

• Fabrice Meriaudeau, LE2I UMR CNRS 6306, Université de Bourgogne, 12 rue de la Fonderie, 71200 Le Creusot, France

Guest Editors

• Luca Giancardo, PAVIS group, Istituto Italiano di Tecnologia (IIT), Via Morego 30, Genova 16163, Italy
• Vincent Paquit, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6075, USA