texture analysis

Textural analysis and artificial intelligence as decision support tools in the diagnosis of multiple sclerosis – a systematic review (2025)

Frontiers in Neuroscience Authors Filip Orzan, Ș. Iancu, L. Dioşan, Z. Bálint Abstract Introduction Magnetic resonance imaging (MRI) is conventionally used for the detection and diagnosis of multiple sclerosis (MS), often complemented by lumbar puncture—a highly invasive method—to validate the diagnosis. Additionally, MRI is periodically repeated to monitor disease progression and treatment efficacy. Recent…

MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment (2023)

Diagnostics Authors B. Boca, C. Caraiani, T. Telecan, R. Pintican, A. Lebovici, I. Andraș, N. Crisan, Alexandru Pavel, L. Dioşan, Z. Bálint, M. Lupșor-Platon, M. Buruian Abstract Background: With the recent introduction of vesical imaging reporting and data system (VI-RADS), magnetic resonance imaging (MRI) has become the main imaging method used for the preoperative…

An Evaluation of Image Texture Descriptors and their Invariant Properties (2022)

Symposium on Symbolic and Numeric Algorithms for Scientific Computing Authors Roxana Sipos-Lascu, L. Dioşan Abstract Image processing applications include image classification, image segmentation, image synthesis and many others. Each such task depends on extracting an effective set of features to characterize the images, and texture analysis has proven to output some of the most…

More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis—A Systematic Review (2022)

Journal of Personalized Medicine Authors T. Telecan, I. Andraș, N. Crisan, Lorin Giurgiu, E. Căta, C. Caraiani, A. Lebovici, B. Boca, Z. Bálint, L. Dioşan, M. Lupșor-Platon Abstract Introduction: Multiparametric magnetic resonance imaging (mpMRI) is the main imagistic tool employed to assess patients suspected of harboring prostate cancer (PCa), setting the indication for targeted…