To investigate the effect of image preprocessing, in respect to intensity inhomogeneity correction and noise filtering, on robustness reproducibility radiomics features extracted from Glioblastoma (GBM) tumor multimodal MR images (mMRI). In this study, for each patient 1461 were GBM subregions (i.e., edema, necrosis, enhancement, tumor) mMRI FLAIR, T1, T1C, T2) volumes five preprocessing combinations (in total 116 880 features). The assessed under four comparisons: (a) Baseline versus...

The Sharp-van der Heijde score (SvH) is crucial for assessing joint damage in rheumatoid arthritis (RA) through radiographic images. However, manual scoring time-consuming and subject to variability. This study proposes a multistage deep learning model predict the Overall Sharp Score (OSS) from hand X-ray framework involves four stages: image preprocessing, segmentation with UNet, identification via YOLOv7, OSS prediction utilizing custom Vision Transformer (ViT). Evaluation metrics included...

This retrospective study has been conducted to validate the performance of deep learning-based survival models in glioblastoma (GBM) patients alongside Cox proportional hazards model (CoxPH) and random forest (RSF). Furthermore, effect hyperparameters optimization methods on improving prediction accuracy was investigated. Of 305 cases, 260 GBM were included our analysis based following criteria: demographic information (i.e., age, Karnofsky score, gender, race), tumor characteristic...

The appearance of microcalcifications in mammograms is one the early signs breast cancer. So, detection microcalcification clusters (MCCs) can be helpful for cancer diagnosis and better treatment In this paper a computer method has been proposed to support radiologists MCCs digital mammography. First, order facilitate improve step, mammogram images have enhanced with wavelet transformation morphology operation. Then segmentation suspicious MCCs, two methods investigated. considered are:...

Introduction Breast cancer is one of the most common types among women. Early detection breast key to reducing associated mortality rate. The presence microcalcifications clusters (MCCs) earliest signs cancer. Due poor imaging contrast mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially MCCs. In order improve detection, image enhancement methods are often used aid radiologists. this paper, a new method was presented for accurate early MCCs in...

<title>Abstract</title> The total Sharp-van der Heijde score (TSS) is crucial for assessing the joint damage severity in rheumatoid arthritis (RA). Manual scoring often time-consuming and subjective, leading to variability. This study introduces an Automated Radiographic Sharp Scoring (ARTSS) framework that leverages deep learning analyze full-hand X-ray images, aiming reduce inter- intra-observer A key innovation its ability handle patients with disappearance variable-length image...