AIMC Topic: Humans

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Femoral image segmentation based on two-stage convolutional network using 3D-DMFNet and 3D-ResUnet.

Computer methods and programs in biomedicine
OBJECTIVE: The femur is a typical human long bone with an irregular spatial structure. Femoral fractures are the most common occurrence in middle-aged and older adults. The structure of human bone tissue is very complex, and there are significant dif...

Anticipation for surgical workflow through instrument interaction and recognized Signals.

Medical image analysis
Surgical workflow anticipation is an essential task for computer-assisted intervention (CAI) systems. It aims at predicting the future surgical phase and instrument occurrence, providing support for intra-operative decision-support system. Recent stu...

MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data.

Computers in biology and medicine
The discovery of cancer subtypes based on unsupervised clustering helps in providing a precise diagnosis, guide treatment, and improve patients' prognoses. Instead of single-omics data, multi-omics data can improve the clustering performance because ...

Cardiovascular Imaging in China: Yesterday, Today, and Tomorrow.

Journal of thoracic imaging
The high prevalence and mortality of cardiovascular diseases in China's large population has increased the use of cardiovascular imaging for the assessment of conditions in recent years. In this study, we review the past 20 years of cardiovascular im...

Artificial intelligence based liver portal tract region identification and quantification with transplant biopsy whole-slide images.

Computers in biology and medicine
Liver fibrosis staging is clinically important for liver disease progression prediction. As the portal tract fibrotic quantity and size in a liver biopsy correlate with the fibrosis stage, an accurate analysis of portal tract regions is clinically cr...

Imbalanced low-rank tensor completion via latent matrix factorization.

Neural networks : the official journal of the International Neural Network Society
Tensor completion has been widely used in computer vision and machine learning. Most existing tensor completion methods empirically assume the intrinsic tensor is simultaneous low-rank in all over modes. However, tensor data recorded from real-world ...

Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: Treatment of acute ischemic stroke is heavily contingent upon time, as there is a strong relationship between time clock and tissue progression. Work has established imaging biomarker assessments as surrogates for time since s...

[Relationship between Image Quality and Reconstruction FOV in Deep Learning Reconstructed Images of CT].

Nihon Hoshasen Gijutsu Gakkai zasshi
In this study, we compared the image quality of deep learning reconstruction (DLR) with that of conventional image reconstruction methods under the same conditions of reconstruction FOV and acquisition dose assuming abdomen computed tomography (CT) i...

Suicidal behaviour prediction models using machine learning techniques: A systematic review.

Artificial intelligence in medicine
BACKGROUND: Early detection and prediction of suicidal behaviour are key factors in suicide control. In conjunction with recent advances in the field of artificial intelligence, there is increasing research into how machine learning can assist in the...

Algorithmic fairness in computational medicine.

EBioMedicine
Machine learning models are increasingly adopted for facilitating clinical decision-making. However, recent research has shown that machine learning techniques may result in potential biases when making decisions for people in different subgroups, wh...