Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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MRI based early Temporal Lobe Epilepsy detection using DGWO based optimized HAETN and Fuzzy-AAL Segmentation Framework (FASF).

This work aims to promote early and accurate diagnosis of Temporal Lobe Epilepsy (TLE) by developing...

Photoacoustic-Integrated Multimodal Approach for Colorectal Cancer Diagnosis.

Colorectal cancer remains a major global health challenge, emphasizing the need for advanced diagnos...

Advancements in the application of MRI radiomics in meningioma.

Meningiomas are among the most common intracranial tumors, and challenges still remain in terms of t...

MRI radiomics model for predicting tumor immune microenvironment types and efficacy of anti-PD-1/PD-L1 therapy in hepatocellular carcinoma.

BACKGROUND: To improve the prediction of immune checkpoint inhibitors (ICIs) efficacy in hepatocellu...

Perilesional dominance: radiomics of multiparametric MRI enhances differentiation of IgG4-Related ophthalmic disease and orbital MALT lymphoma.

BACKGROUND: To develop and validate a diagnostic framework integrating intralesional (ILN) and peril...

Attention-driven hybrid deep learning and SVM model for early Alzheimer's diagnosis using neuroimaging fusion.

Alzheimer's Disease (AD) poses a significant global health challenge, necessitating early and accura...

Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women.

BACKGROUND: Current ultrasound-based screening for endometrial cancer (EC) primarily relies on endom...

Contrast-enhanced mammography-based interpretable machine learning model for the prediction of the molecular subtype breast cancers.

OBJECTIVE: This study aims to establish a machine learning prediction model to explore the correlati...

Multimodal deep learning-based radiomics for meningioma consistency prediction: integrating T1 and T2 MRI in a multi-center study.

BACKGROUND: Meningioma consistency critically impacts surgical planning, as soft tumors are easier t...

Quantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage.

In this study, we explore the potential of ten quantitative (radiofrequency-based) ultrasound parame...

Determination of the oral carcinoma and sarcoma in contrast enhanced CT images using deep convolutional neural networks.

Oral cancer is a hazardous disease and a major cause of morbidity and mortality worldwide. The purpo...

Hybrid model integration with explainable AI for brain tumor diagnosis: a unified approach to MRI analysis and prediction.

Effective treatment for brain tumors relies on accurate detection because this is a crucial health c...

Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques.

Breast cancer remains a major cause of mortality among women, where early and accurate detection is ...

Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.

Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans,...

Brain structural features with functional priori to classify Parkinson's disease and multiple system atrophy using diagnostic MRI.

Clinical two-dimensional (2D) MRI data has seen limited application in the early diagnosis of Parkin...

Attention residual network for medical ultrasound image segmentation.

Ultrasound imaging can distinctly display the morphology and structure of internal organs within the...

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