AIMC Topic: Humans

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DDParcel: Deep Learning Anatomical Brain Parcellation From Diffusion MRI.

IEEE transactions on medical imaging
Parcellation of anatomically segregated cortical and subcortical brain regions is required in diffusion MRI (dMRI) analysis for region-specific quantification and better anatomical specificity of tractography. Most current dMRI parcellation approache...

Modeling Fatigue in Manual and Robot-Assisted Work for Operator 5.0.

IISE transactions on occupational ergonomics and human factors

Teardrop Alignment Changes After Volar Locking Plate Fixation of Distal Radius Fractures With Volar Ulnar Fragments.

Hand (New York, N.Y.)
BACKGROUND: We assessed factors associated with change in radiographic teardrop angle following volar locking plate (VLP) fixation of volarly displaced intra-articular distal radius fractures with volar ulnar fragments (VUF) within the ICUC database....

More Is Not Always Better: Impacts of AI-Generated Confidence and Explanations in Human-Automation Interaction.

Human factors
OBJECTIVE: The study aimed to enhance transparency in autonomous systems by automatically generating and visualizing confidence and explanations and assessing their impacts on performance, trust, preference, and eye-tracking behaviors in human-automa...

Addressing the Contrast Media Recognition Challenge: A Fully Automated Machine Learning Approach for Predicting Contrast Phases in CT Imaging.

Investigative radiology
OBJECTIVES: Accurately acquiring and assigning different contrast-enhanced phases in computed tomography (CT) is relevant for clinicians and for artificial intelligence orchestration to select the most appropriate series for analysis. However, this i...

Optimizing Coronary Computed Tomography Angiography Using a Novel Deep Learning-Based Algorithm.

Journal of imaging informatics in medicine
Coronary computed tomography angiography (CCTA) is an essential part of the diagnosis of chronic coronary syndrome (CCS) in patients with low-to-intermediate pre-test probability. The minimum technical requirement is 64-row multidetector CT (64-MDCT)...

From CNN to Transformer: A Review of Medical Image Segmentation Models.

Journal of imaging informatics in medicine
Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely ad...

Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique.

Journal of imaging informatics in medicine
Image segmentation is a crucial task in computer vision and image processing, with numerous segmentation algorithms being found in the literature. It has important applications in scene understanding, medical image analysis, robotic perception, video...

Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis.

Journal of imaging informatics in medicine
Due to the increasing interest in the use of artificial intelligence (AI) algorithms in hepatocellular carcinoma detection, we performed a systematic review and meta-analysis to pool the data on diagnostic performance metrics of AI and to compare the...

Pan-cancer image segmentation based on feature pyramids and Mask R-CNN framework.

Medical physics
BACKGROUND: Cancer, a disease with a high mortality rate, poses a great threat to patients' physical and mental health and can lead to huge medical costs and emotional damage. With the continuous development of artificial intelligence technologies, d...