نتایج جستجو برای: radiomic prediction mri
تعداد نتایج: 357714 فیلتر نتایج به سال:
Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in general, the size, shape, texture, intensity, margin, and other aspects of the imaging features of nodules and lesions. Efforts are ongoing for ...
Alzheimer’s disease is a non-reversible, non-curable, and progressive neurological disorder that induces the shrinkage death of specific neuronal population associated with memory formation retention. It frequently occurring mental illness occurs in about 60%–80% cases dementia. usually observed between people age group 60 years above. Depending upon severity symptoms patients can be categorize...
Background: Assessment of renal lesions and deficiency accurately remains critical in the diagnosis congenital anomalies kidneys urinary tracts (CAKUT) children. Advanced imaging such as Magnetic resonance Imaging (MRI) Diffusion weighted (DWI) allows structural functional insufficiency to be detected. Currently, radiomics machine learning models are being explored full-automated diagnostic too...
One of the most common challenges in brain MRI scans is to perform different sequences depending on type and properties tissues. In this paper, we propose a generative method translate T2-Weighted (T2W) Magnetic Resonance Imaging (MRI) volume from T2-weight-Fluid-attenuated-Inversion-Recovery (FLAIR) vice versa using Generative Adversarial Networks (GAN). To evaluate proposed method, novel eval...
Magnetic Resonance Imaging (MRI) is the standard of care in the clinic for diagnosis and follow up of Soft Tissue Sarcomas (STS) which presents an opportunity to explore the heterogeneity inherent in these rare tumors. Tumor heterogeneity is a challenging problem to quantify and has been shown to exist at many scales, from genomic to radiomic, existing both within an individual tumor, between t...
Purpose of the study. Comparing magnetic resonance imaging (MRI) abilities in differential diagnostic three types primary extra‑ axial brain tumors (benign and malignant meningiomas, neuromas) based on standard semiotics radiomic features. Patients methods. Retrospective research included 66 patients with extra‑a xial who were divided into two groups: instructional (39 patients) valid (27 patie...
Background: In patients with soft-tissue sarcomas of the extremities, treatment decision is currently regularly based on tumor grading and size. The imaging-based analysis may pose an alternative way to stratify patients’ risk. this work, we compared value MRI-based radiomics expert-derived semantic imaging features for prediction overall survival (OS). Methods: Fat-saturated T2-weighted sequen...
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