AIMC Topic: Deep Learning

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Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.

Journal of imaging informatics in medicine
Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the performance of TotalSegmentator, a state-of-the-art adult-trained CT organ segmentation model, on a s...

Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.

Journal of imaging informatics in medicine
To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-V). Three ...

Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography.

European radiology
OBJECTIVE: To evaluate radiation dose and image quality of a double-low CCTA protocol reconstructed utilizing high-strength deep learning image reconstructions (DLIR-H) compared to standard adaptive statistical iterative reconstruction (ASiR-V) proto...

Hallux valgus and pes planus: Correlation analysis using deep learning-assisted radiographic angle measurements.

Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons
BACKGROUND: The relationship between hallux valgus (HV) and pes planus remains unresolved. This study aims to determine the correlation between HV and pes planus using a deep learning (DL) model to measure radiographic angle parameters.

Maxillofacial bone movements-aware dual graph convolution approach for postoperative facial appearance prediction.

Medical image analysis
Postoperative facial appearance prediction is vital for surgeons to make orthognathic surgical plans and communicate with patients. Conventional biomechanical prediction methods require heavy computations and time-consuming manual operations which ha...

Automated Deep Learning-Based Finger Joint Segmentation in 3-D Ultrasound Images With Limited Dataset.

Ultrasonic imaging
Ultrasound imaging has shown promise in assessing synovium inflammation associated early stages of rheumatoid arthritis (RA). The precise identification of the synovium and the quantification of inflammation-specific imaging biomarkers is a crucial a...

Deep learning models for predicting plant uptake of emerging contaminants by including the role of plant macromolecular compositions.

Journal of hazardous materials
Deep learning models can predict uptake of emerging contaminants in plants with improved accuracy because they leverage advanced data-driven approaches to capture non-linear relationships that traditional models struggle to address. Traditional model...

Lazy Resampling: Fast and information preserving preprocessing for deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Preprocessing of data is a vital step for almost all deep learning workflows. In computer vision, manipulation of data intensity and spatial properties can improve network stability and can provide an important source of gen...

NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to ha...