AIMC Topic: Magnetic Resonance Imaging
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Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis.
Scientific reports
Aug 11, 2025
Recent innovations in medical imaging have markedly improved brain tumor identification, surpassing conventional diagnostic approaches that suffer from low resolution, radiation exposure, and limited contrast. Magnetic Resonance Imaging (MRI) is pivo...
Multimodal radiomics in glioma: predicting recurrence in the peritumoural brain zone using integrated MRI.
BMC medical imaging
Aug 11, 2025
BACKGROUND: Gliomas exhibit a high recurrence rate, particularly in the peritumoural brain zone after surgery. This study aims to develop and validate a radiomics-based model using preoperative fluid-attenuated inversion recovery (FLAIR) and T1-weigh...
Enhancing meningioma tumor classification accuracy through multi-task learning approach and image analysis of MRI images.
PloS one
Aug 11, 2025
BACKGROUND: Accurate classification of meningioma brain tumors is crucial for determining the appropriate treatment plan and improving patient outcomes. However, this task is challenging due to the slow-growing nature of these tumors and the potentia...
Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.
Scientific reports
Aug 10, 2025
Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory loss, and behavioral changes. Early diagnosis, particularly identifying Early Mild Cognitive Impairment (EMCI), is vital for managing the disease and ...
Prediction of cervical cancer lymph node metastasis based on multisequence magnetic resonance imaging radiomics and deep learning features: a dual-center study.
Scientific reports
Aug 10, 2025
Cervical cancer is a leading cause of death from malignant tumors in women, and accurate evaluation of occult lymph node metastasis (OLNM) is crucial for optimal treatment. This study aimed to develop several predictive models-including Clinical mode...
Advanced dynamic ensemble framework with explainability driven insights for precision brain tumor classification across datasets.
Scientific reports
Aug 8, 2025
Accurate detection of brain tumors remains a significant challenge due to the diversity of tumor types along with human interventions during diagnostic process. This study proposes a novel ensemble deep learning system for accurate brain tumor classi...
BCDCNN: breast cancer deep convolutional neural network for breast cancer detection using MRI images.
Scientific reports
Aug 8, 2025
Breast cancer (BC) is a kind of cancer that is created from the cells in breast tissue. This is a primary cancer that occurs in women. Earlier identification of BC is significant in the treatment process. To lessen unwanted biopsies, Magnetic Resonan...
MRI-based radiomics for preoperative T-staging of rectal cancer: a retrospective analysis.
International journal of colorectal disease
Aug 8, 2025
PUROPOSE: Preoperative T-staging in rectal cancer is essential for treatment planning, yet conventional MRI shows limited accuracy (~ 60-78). Our study investigates whether radiomic analysis of high-resolution T2-weighted MRI can non-invasively impro...
Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study.
PloS one
Aug 8, 2025
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive nature and association with other chronic diseases make...
Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.
Alzheimer's research & therapy
Aug 7, 2025
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...
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