Radiology

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

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A deep learning approach for early prediction of breast cancer neoadjuvant chemotherapy response on multistage bimodal ultrasound images.

Neoadjuvant chemotherapy (NAC) is a systemic and systematic chemotherapy regimen for breast cancer p...

Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.

PURPOSE: Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression...

Multi-parametric MRI combined with radiomics for the diagnosis and grading of endometrial fibrosis.

PURPOSE: To evaluate the application of multi-parametric MRI (MP-MRI) combined with radiomics in dia...

Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.

OBJECTIVES: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on pr...

Classifying the molecular subtype of breast cancer using vision transformer and convolutional neural network features.

PURPOSE: Identification of the molecular subtypes in breast cancer allows to optimize treatment stra...

Automatic Measurement of Frontomaxillary Facial Angle in Fetal Ultrasound Images Using Deep Learning.

Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays ...

Modernizing Neuro-Oncology: The Impact of Imaging, Liquid Biopsies, and AI on Diagnosis and Treatment.

Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are ...

Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.

BACKGROUND: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate th...

CDCG-UNet: Chaotic Optimization Assisted Brain Tumor Segmentation Based on Dilated Channel Gate Attention U-Net Model.

Brain tumours are one of the most deadly and noticeable types of cancer, affecting both children and...

Multimodal multiview bilinear graph convolutional network for mild cognitive impairment diagnosis.

Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's d...

Deep proximal gradient network for absorption coefficient recovery in photoacoustic tomography.

The optical absorption properties of biological tissues in photoacoustic (PA) tomography are typical...

A data driven approach for soft tissue biomarker identification linked to Chiari-like malformation and syringomyelia.

Canine Chiari-like malformation (CM) is a neuroanatomical condition associated with conformational c...

Transforming Healthcare: Artificial Intelligence (AI) Applications in Medical Imaging and Drug Response Prediction.

Artificial intelligence (AI) offers a broad range of enhancements in medicine. Machine learning and ...

Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.

BACKGROUND & AIMS: Accurate multi-classification is a prerequisite for appropriate management of foc...

Endovascular robotics: technical advances and future directions.

Endovascular interventions excel in treating cardiovascular diseases in a minimally invasive manner,...

[Application and considerations of artificial intelligence and neuroimaging in the study of brain effect mechanisms of acupuncture and moxibustion].

Electroencephalography (EEG) and magnetic resonance imaging (MRI), as neuroimaging technologies, pro...

Towards contrast-agnostic soft segmentation of the spinal cord.

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sec...

ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus.

In image segmentation for medical image analysis, effective upsampling is crucial for recovering spa...

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