6533b853fe1ef96bd12ac19c
RESEARCH PRODUCT
Computer-Aided Detection for Prostate Cancer Detection based on Multi-Parametric Magnetic Resonance Imaging
Mojdeh RastgooGuillaume LemaitreRobert MartíFabrice Meriaudeausubject
Malemedicine.medical_specialtySource codemedia_common.quotation_subject[INFO.INFO-IM] Computer Science [cs]/Medical ImagingContrast MediaCAD[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Prostatemedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML][SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingmedia_commonMulti parametricModality (human–computer interaction)[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingmedicine.diagnostic_testbusiness.industryProstatic NeoplasmsCancerMagnetic resonance imagingmedicine.diseaseMagnetic Resonance Imaging[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]3. Good healthmedicine.anatomical_structureRadiologybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgerydescription
International audience; Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. In the last decades, new imaging techniques based on magnetic resonance imaging (MRI) have been developed improving diagnosis. In practice, diagnosis is affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and diagnosis (CAD) systems are being designed to help radiologists in their clinical practice. We propose a CAD system taking advantage of all MRI modalities (i.e., T2-W-MRI, DCE-MRI, diffusion weighted (DW)-MRI, MRSI). The aim of this CAD system was to provide a probabilistic map of cancer location in the prostate. We extensively tested our proposed CAD using different fusion approaches to combine the features provided by each modality. The source code and the dataset have been released.
year | journal | country | edition | language |
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2017-07-11 |