Advances in Computer-Aided Detection and Diagnosis

Call for Papers

Computer-aided diagnosis (CAD) systems are computer programs to detect and/or diagnose various lesions in various medical imaging modalities and in various body organs, from breast cancer in breast imaging, to lung cancer in chest imaging, to colon cancer in abdominal imaging, and to brain tumor in brain imaging. CAD is important in clinical practice because clinicians can employ the outputs of these computer systems as a “second opinion” to improve their detection and diagnosis accuracy.

Recent years have seen a rapid progress in CAD technique development, applications, and evaluation. We thus invite researchers to contribute both original research and review papers to present novel techniques and methodologies in computer-aided diagnosis. The focus will be on new key techniques in CAD systems, computerized detection systems, computerized diagnosis systems, CAD evaluation methodologies, and CAD clinical applications. Potential topics include, but are not limited to:

• Key techniques and their effects on CAD schemes, including lesion enhancement, lesion segmentation, lesion prescreening, feature selection, classifier design, algorithm validation, image database, and establishment of reference standards
• CAD in breast imaging, including detection and diagnosis of breast masses, microcalcifications, and architecture distortions in screen film and full field digital mammography, digital breast tomosynthesis, ultrasound imaging, and magnetic resonance imaging
• CAD in chest imaging, including detection and diagnosis of lung nodule, interstitial lung diseases, pulmonary embolism, and emphysema in chest radiography, thoracic CT and PET/CT, and measurement of change in size of lung nodule
• CAD for detection of polyps in CT colonography
• Other emerging CAD systems, including CAD for brain tumor in MRI, cerebrovascular diseases, eye diseases, bone diseases, and prostate cancer
• Assessment and clinical utility of CAD systems

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/ according to the following timetable:

Lead Guest Editor

• Qiang Li, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, Durham, NC, USA

Guest Editors

• Lubomir Hadjiiski, Department of Radiology, University of Michigan, Ann Arbor, MI, USA
• Kensaku Mori, Department of Media Science, Graduate School of Information Science, Nagoya University, Nagoya, Japan
• Walter O’Dell, Department of Radiation Oncology, University of Florida Shands Cancer Center, Gainesville, FL, USA