AIMC Topic: Magnetic Resonance Imaging

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Optimizing and evaluating robustness of AI for brain metastasis detection and segmentation via loss functions and multi-dataset training.

Biomedical physics & engineering express
. Accurate detection and segmentation of brain metastases (BM) from MRI are critical for the appropriate management of cancer patients. This study investigates strategies to enhance the robustness of artificial intelligence (AI)-based BM detection an...

Developing and external validating a prediction model using machine learning and logistic regression: informing the surgical approach for robotic surgery based on preoperative MRI.

Journal of robotic surgery
BACKGROUND: Preoperative prediction of surgical difficulty in robotic-assisted total mesorectal excision for rectal cancer remains challenging. While pelvic anatomical parameters measured by MRI have been associated with surgical complexity in laparo...

GTV segmentation in MRI guided radiotherapy with promptable foundation models.

Physics in medicine and biology
. Magnetic resonance imaging (MRI) guided radiotherapy requires the delineation of gross tumor volumes (GTV) in daily MRI from MRI-linacs. Specialized models have been developed for this task for certain tumors. This study investigated an alternative...

Deep learning-based MRI model for predicting P53-mutated hepatocellular carcinoma.

BMC medical imaging
BACKGROUND: The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-based deep learning m...

MRI and PET-Based Machine Learning Radiomics for Metastasis Prediction in Pancreatic Ductal Adenocarcinoma: A Systematic Review.

Journal of gastrointestinal cancer
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor survival, driven in part by early metastatic spread. Conventional imaging lacks sufficient precision to predict metastasis accurately. Machine learning (ML)-bas...

cMeta-INR: cohort-informed meta-learning-based implicit neural representation for deformable registration-driven real-time volumetric MRI estimation.

Physics in medicine and biology
Rapid and accurate reconstruction of high-quality three-dimensional magnetic resonance (MR) images from undersampled-space data with variable sampling patterns remains a challenge due to limited available information and the need to preserve rich ana...

Ratio maps of T1w/T2w MRI signal intensity do not improve deep-learning segmentation of pediatric brain tumors.

PloS one
INTRODUCTION: T1w/T2w ratio mapping, combining voxel-wise signal intensities in T1-weighted (T1w) and T2-weighted (T2w) structural MRI, has been used to investigate cortical architecture in the brain, but has also shown promise in tissue discriminati...

Association of Brain Age With Physical Disability and Cognitive Impairment in People With Multiple Sclerosis of the Same Age.

Neurology
BACKGROUND AND OBJECTIVES: The brain-predicted age difference (brain-PAD) is a novel marker of neurodegeneration in multiple sclerosis (MS). Brain-PAD has been associated with clinical disability in heterogeneous MS patient cohorts of varying ages an...

Incorporating multi-modal prompt learning into foundation models enhances predictability of visual fMRI responses to dynamic natural stimuli.

Journal of neural engineering
. Modeling neural encoding of visual stimuli often uses deep neural networks (DNNs) to predict human brain response to external stimuli. However, each DNN depends on networks tailored for computer vision tasks, resulting in suboptimal brain correspon...

Regional-aware and sequence-informed multi-decoder network for robust brain glioma segmentation in multi-parametric MRI.

Computers in biology and medicine
Accurate segmentation of glioblastoma subregions from multi-parametric MRI is essential for diagnosis, surgical planning, and treatment monitoring in neuro-oncology. However, effective delineation of surrounding non-enhancing FLAIR hyperintensity, no...