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Computer-Aided Diagnosis of Cancer by Magnetic Resonance Spectroscopy
Comparison of MRS analysis using three different dataset reduction schemes. The white box corresponds to the potential cancer space defined from whole-mount histological sections. Colors correspond to the classification of tissue: Red = cancerous, blue = benign, green = indeterminate. Left: z-score; Middle: Principal component analysis (PCA); Right:...
Published: 12/8/2021
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Inventor(s): Anant Madabhushi, Michael Feldman, John Tomaszewski, Satish Viswanath, Pallavi Tiwari, Robert Toth, Mark Rosen
Keywords(s): Imaging, Prostate Cancer
Category(s): Technology Classifications > Healthcare & Life Sciences, Technology Classifications > Diagnostics, Technology Classifications > Medical Imaging, Technology Classifications > Cancer, Technology Classifications > Artificial Intelligence & Machine Learning, Technology Classifications > Software & Algorithms, Technology Classifications > Software & Copyright
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Automated Detection and Classification of Tumors from Digitized Histological Tissue Specimens
Flowchart illustration of the working of the algorithm Invention Summary: Computer-aided diagnosis (CAD) systems can automatically sort digitized medical images which can otherwise be a time-consuming process.Researchers at Rutgers have developed a CAD method to automatically distinguish between tumor and benign regions in digitized prostate histology....
Published: 12/8/2021
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Inventor(s): Anant Madabhushi, Michael Feldman, John Tomaszewski
Keywords(s): Cancer biomarkers, Imaging
Category(s): Technology Classifications > Healthcare & Life Sciences, Technology Classifications > Diagnostics, Technology Classifications > Software & Copyright, Technology Classifications > Software & Algorithms, Technology Classifications > Artificial Intelligence & Machine Learning, Technology Classifications > Cancer, Technology Classifications > Medical Imaging
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Hierarchical Computer-Aided Detection of Abnormal Regions in Medical Images
Receiver operator characteristic curves for detection of prostate cancer at various weights (T) in histological (top) and MRI (bottom) images. Classification is based on multiplicative weighted maximum a posteriori (MWMAP) estimation with iterated conditional modes (ICM). The regions labeled as malignant at three weights are highlighted in green (histology)...
Published: 12/8/2021
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Inventor(s): James Monaco, Anant Madabhushi, Michael Feldman, John Tomaszewski
Keywords(s): Imaging, Prostate Cancer
Category(s): Technology Classifications > Healthcare & Life Sciences, Technology Classifications > Diagnostics, Technology Classifications > Software & Copyright, Technology Classifications > Cancer, Technology Classifications > Software & Algorithms
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