AIMC Topic: Image Processing, Computer-Assisted

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The stability of oncologic MRI radiomic features and the potential role of deep learning: a review.

Physics in medicine and biology
The use of MRI radiomic models for the diagnosis, prognosis and treatment response prediction of tumors has been increasingly reported in literature. However, its widespread adoption in clinics is hampered by issues related to features stability. In ...

Automatic hemorrhage segmentation on head CT scan for traumatic brain injury using 3D deep learning model.

Computers in biology and medicine
The most common cause of long-term disability and death in young adults is a traumatic brain injury. The decision for surgical intervention for craniotomy is dependent on the injury type and the patient's neurologic exam. The potential subtypes of in...

Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE/OBJECTIVE(S): Precise segmentation of clinical target volumes (CTV) in breast cancer is indispensable for state-of-the art radiotherapy. Despite international guidelines, significant intra- and interobserver variability exists, negatively imp...

Deep learning-based single image super-resolution for low-field MR brain images.

Scientific reports
Low-field MRI scanners are significantly less expensive than their high-field counterparts, which gives them the potential to make MRI technology more accessible all around the world. In general, images acquired using low-field MRI scanners tend to b...

Improving high frequency image features of deep learning reconstructions via k-space refinement with null-space kernel.

Magnetic resonance in medicine
PURPOSE: Deep learning (DL) based reconstruction using unrolled neural networks has shown great potential in accelerating MRI. However, one of the major drawbacks is the loss of high-frequency details and textures in the output. The purpose of the st...

CADxReport: Chest x-ray report generation using co-attention mechanism and reinforcement learning.

Computers in biology and medicine
BACKGROUND: Automated generation of radiological reports for different imaging modalities is essentially required to smoothen the clinical workflow and alleviate radiologists' workload. It involves the careful amalgamation of image processing techniq...

XctNet: Reconstruction network of volumetric images from a single X-ray image.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Conventional Computed Tomography (CT) produces volumetric images by computing inverse Radon transformation using X-ray projections from different angles, which results in high dose radiation, long reconstruction time and artifacts. Biologically, prio...

Automatic measurement of fetal head circumference using a novel GCN-assisted deep convolutional network.

Computers in biology and medicine
The growth of the fetus can be effectively monitored by measuring the fetal head circumference (HC) in ultrasound images. Moreover, it is the key to assessing the fetus's health. Ultrasound fetal head image boundary is blurred. The ultrasound sound s...

A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system.

Scientific reports
Automated classification and detection of brain abnormalities like a tumor(s) in reconstructed microwave (RMW) brain images are essential for medical application investigation and monitoring disease progression. This paper presents the automatic clas...

Artificial Intelligence Radiotherapy Planning: Automatic Segmentation of Human Organs in CT Images Based on a Modified Convolutional Neural Network.

Frontiers in public health
OBJECTIVE: Precise segmentation of human organs and anatomic structures (especially organs at risk, OARs) is the basis and prerequisite for the treatment planning of radiation therapy. In order to ensure rapid and accurate design of radiotherapy trea...