A Computer-Aided Diagnostic System for the Early Detection of Prostate Cancer Using Diffusion-Weighted Magnetic Resonance Imaging

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

The area of medical image analysis has always been an inspiring application of the various computer vision and pattern recognition theories and approaches. Due to its challenging aspects, prostate cancer diagnosis via magnetic resonance images (MRI) is one of the most popular in the medical imaging research community. Several studies have highlighted the need to develop a robust and accurate computer-aided diagnosis (CAD) system to detect and localize suspicious lesions in the prostate area. Accordingly, this thesis addresses the topic of MRI-based prostate cancer detection and localization. We begin with an extended review of the state-of-the-art CAD systems, identifying the gaps and limitations of the di?erent approaches. Afterward, we propose our two contributions for 1) Computer-aided design system or prostate cancer detection; and 2) Automatic prostate cancer tumor detection. In the first contribution, we employ a classical pattern recognition and machine learning approach to classify benign and malignant subjects. In this system, we utilize Diffusion-weighted (DW) images at different magnetic field strengths to produce a global apparent diffusion coefficient (ADC) map for each subject. These maps are then reshaped and classified using a shallow neural network. In the second contribution, we propose a deep convolutional encoder-decoder architecture to segment tumors in T2-weighted (T2W) images. We also provide a multi-channel approach to exploit the 3D information in the MR images without

روابط وملفات

التعريف والنوع

رقم الوثيقة

0be42842-e9dc-4a2c-a96d-d717fc476ca8

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

2283227_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Fatma Taher","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Naoufel Werghi","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Ruba Hassan Alkadi ","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

English

المصدر والدورية

اسم المصدر

A Computer-Aided Diagnostic System for the Early Detection of Prostate Cancer Using Diffusion-Weighted Magnetic Resonance Imaging

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

magnetic resonance imaging computer-aided diagnosis prostate cancer deep learning pattern recognition semantic segmentation

إشراف وإعداد

الإشراف

Fatma Taher, Naoufel Werghi

الإعداد

Ruba Hassan Alkadi

الاقتباسات الببليوغرافية