Computer-Aided Diagnosis Systems for Acute Renal Transplant Rejection: Challenges and Methodologies
This chapter overviews one of the most critical problems in urology, namely detection of acute renal transplant rejection. Developing an effective, fast, and accurate computer-aided diagnosis (CAD) system for early detection of acute renal rejection is of
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Abstract This chapter overviews one of the most critical problems in urology, namely detection of acute renal transplant rejection. Developing an effective, fast, and accurate computer-aided diagnosis (CAD) system for early detection of acute renal rejection is of great clinical importance for the management of these patients. For this reason, CAD systems for early detection of renal transplant rejection have been investigated in a huge number of research studies using different image modalities, such as ultrasound (US), magnetic resonance imaging (MRI), computed tomography (CT), and radionuclide imaging. A typical CAD system for kidney diagnosis consists of a set of processing steps including, but not limited to, image registration to account for kidney motion, segmentation of the kidney and/or its compartments (e.g., cortex, medulla), construction of agent kinetic curves, functional parameters estimation, and diagnosis and assessment of the kidney status. Due to the widespread popularity of US and MRI, this chapter overviews the current state-of-the-art CAD systems that have been developed for kidney diagnosis using these two image modalities. In addition, the chapter addresses several challenges that researchers face in developing efficient, fast, and reliable CAD systems for early detection of kidney diseases.
M. Mostapha • F. Khalifa • A. Alansary • A. Soliman BioImaging laboratory, Bioengineering Department and with the Electrical and Computer Engineering Department, University of Louisville, Louisville, KY 40292, USA J. Suri Biomedical Technologies, Inc., Roseville CA, USA A.S. El-Baz (*) BioImaging laboratory, Bioengineering Department, University of Louisville, Louisville, KY 40292, USA e-mail: [email protected] A.S. El-Baz et al. (eds.), Abdomen and Thoracic Imaging: An Engineering & Clinical Perspective, DOI 10.1007/978-1-4614-8498-1_1, © Springer Science+Business Media New York 2014
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Introduction Early detection of kidney rejection is important for clinical management in patients with transplanted kidneys [1]. In the USA, approximately 17,736 renal transplants are performed annually [2], and given the limited number of donors, transplanted kidney salvage is an important goal. Renal transplantation complications could be divided into 6 classes: urologic complications, fluid collections, vascular complications, neoplasms, recurrent native renal disease, and graft dysfunction [3]. Urologic complications include urine leaks associated with discharged urinomas, which have different sizes and occurs within 2 weeks from transplantation. Also, transplant patients face the high risk of developing calculous disease and urinary obstruction. Around transplantation fluid collections have been usually recorded in up to 50 % of renal transplantations and include urinomas, hematomas, lymphoceles, and abscesses. The size, location, and the growth possibility of these collections greatly influence their clinical relevance [4]. vascular complications include transplanted artery s
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