Isbn: 9786207841776 - kidney cancer detection using image processing techniques: implementation of computer aided diagnosis for kidney cancer detection (11 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. In English.

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Taschenbuch. Condición: Neu. KIDNEY CANCER DETECTION USING IMAGE PROCESSING TECHNIQUES | IMPLEMENTATION OF COMPUTER AIDED DIAGNOSIS FOR KIDNEY CANCER DETECTION | Subraja R. (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207841776 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 76 pp. Englisch.

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic procedures for early detection and diagnosis are crucial. Some difficulties with manual segmentation have necessitated the use of deep learning models to assist clinicians in effectively recognizing and segmenting cancer. Probabilistic Convolutional Neural Network (PCNN) particularly convolutional neural networks, has produced outstanding success in classifying and segmenting images. In this project, image filtering on MRI kidney images is carried out using Bilateral Anisotropic Diffusion Filter algorithm. This proposed preprocessing technique provides high Peak Signal to Noise Ratio) PSNR and low Mean Square Error (MSE). Image enhancement on MRI kidney images is carried out using Edge Preservation-Contrast Limited Adaptive Histogram Equalization (EP-CLAHE) algorithm. The EP-CLAHE is used to improve contrast and brightness. MRI kidney image segmentation is carried out using Improved Fast Fuzzy C Means Clustering (IFFCMC) algorithm. IFFCMC is used to segment on the kidney cancer pixels and suppress other pixels on MRI kidney image.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic procedures for early detection and diagnosis are crucial. Some difficulties with manual segmentation have necessitated the use of deep learning models to assist clinicians in effectively recognizing and segmenting cancer. Probabilistic Convolutional Neural Network (PCNN) particularly convolutional neural networks, has produced outstanding success in classifying and segmenting images. In this project, image filtering on MRI kidney images is carried out using Bilateral Anisotropic Diffusion Filter algorithm. This proposed preprocessing technique provides high Peak Signal to Noise Ratio) PSNR and low Mean Square Error (MSE). Image enhancement on MRI kidney images is carried out using Edge Preservation-Contrast Limited Adaptive Histogram Equalization (EP-CLAHE) algorithm. The EP-CLAHE is used to improve contrast and brightness. MRI kidney image segmentation is carried out using Improved Fast Fuzzy C Means Clustering (IFFCMC) algorithm. IFFCMC is used to segment on the kidney cancer pixels and suppress other pixels on MRI kidney image.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…