AIMC Topic: Humans

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A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images.

IEEE/ACM transactions on computational biology and bioinformatics
Eyelid malignant melanoma (MM) is a rare disease with high mortality. Accurate diagnosis of such disease is important but challenging. In clinical practice, the diagnosis of MM is currently performed manually by pathologists, which is subjective and ...

Progressive Feature Fusion Attention Dense Network for Speckle Noise Removal in OCT Images.

IEEE/ACM transactions on computational biology and bioinformatics
Although deep learning for Big Data analytics has achieved promising results in the field of optical coherence tomography (OCT) image denoising, the low recognition rate caused by complex noise distribution and a large number of redundant features is...

Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...

Human-Robot Collaboration With a Corrective Shared Controlled Robot in a Sanding Task.

Human factors
OBJECTIVE: Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.

Deep learning MR reconstruction in knees and ankles in children and young adults. Is it ready for clinical use?

Skeletal radiology
OBJECTIVE: To evaluate the diagnostic performance and image quality of accelerated Turbo Spin Echo sequences using deep-learning (DL) reconstructions compared to conventional sequences in knee and ankle MRIs of children and young adults.

Automated 3D Cobb Angle Measurement Using U-Net in CT Images of Preoperative Scoliosis Patients.

Journal of imaging informatics in medicine
To propose a deep learning framework "SpineCurve-net" for automated measuring the 3D Cobb angles from computed tomography (CT) images of presurgical scoliosis patients. A total of 116 scoliosis patients were analyzed, divided into a training set of 8...

INVESTIGATION OF HAND TREMOR SUPPRESSION BY A CUSTOMIZED PASSIVE SURGICAL SUPPORT ROBOT DURING INTERNAL LIMITING MEMBRANE PEELING.

Retina (Philadelphia, Pa.)
PURPOSE: To construct a quantitative evaluation system for hand tremor during internal limiting membrane (ILM) peeling and investigate changes in hand tremor attributable to the use of the customized passive surgical support robot.

Euclidean-Distance-Preserved Feature Reduction for efficient person re-identification.

Neural networks : the official journal of the International Neural Network Society
Person Re-identification (Re-ID) aims to match person images across non-overlapping cameras. The existing approaches formulate this task as fine-grained representation learning with deep neural networks, which involves extracting image features using...

DCE-Qnet: deep network quantification of dynamic contrast enhanced (DCE) MRI.

Magma (New York, N.Y.)
INTRODUCTION: Quantification of dynamic contrast-enhanced (DCE)-MRI has the potential to provide valuable clinical information, but robust pharmacokinetic modeling remains a challenge for clinical adoption.

Deep learning-based computer-aided detection of ultrasound in breast cancer diagnosis: A systematic review and meta-analysis.

Clinical radiology
PURPOSE: The aim of this meta-analysis was to assess the diagnostic performance of deep learning (DL) and ultrasound in breast cancer diagnosis. Additionally, we categorized the included studies into two subgroups: B-mode ultrasound diagnostic subgro...