Texture and shape analysis of diffusion‐weighted imaging for thyroid nodules classification using machine learning

• Published in: Medical physics (Lancaster) Vol. 49; no. 2; pp. 988 - 999
• Main Authors: Sharafeldeen, Ahmed, Elsharkawy, Mohamed, Khaled, Reem, Shaffie, Ahmed, Khalifa, Fahmi, Soliman, Ahmed, Abdel Razek, Ahmed Abdel khalek, Hussein, Manar Mansour, Taman, Saher, Naglah, Ahmed, Alrahmawy, Mohammed, Elmougy, Samir, Yousaf, Jawad, Ghazal, Mohammed, El‐Baz, Ayman
• Format: Journal Article
• Language: English
• Published: United States 01.02.2022
• Subjects: apparent diffusion coefficient (ADC); Diffusion Magnetic Resonance Imaging; diffusion‐weighted MRI; Humans; Machine Learning; Magnetic Resonance Imaging; neural network (NN); Retrospective Studies; spherical harmonic (SH); T2‐MRI; textural analysis; Thyroid Nodule - diagnostic imaging; thyroid tumors; thyroid tumors; T2-MRI; apparent diffusion coefficient (ADC); neural network (NN); spherical harmonic (SH); textural analysis; diffusion-weighted MRI

Purpose To assess whether the integration between (a) functional imaging features that will be extracted from diffusion‐weighted imaging (DWI); and (b) shape and texture imaging features as well as volumetric features that will be extracted from T2‐weighted magnetic resonance imaging (MRI) can nonin...