AIMC Topic: Deep Learning
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Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.
Scientific reports
Apr 6, 2025
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...
Using artificial intelligence system for assisting the classification of breast ultrasound glandular tissue components in dense breast tissue.
Scientific reports
Apr 6, 2025
To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound analysis models for the classification of glandular tissue components (GTC) in dense breast tissue. A total of 1,848 healthy women with mammograms classi...
Hybrid vision GNNs based early detection and protection against pest diseases in coffee plants.
Scientific reports
Apr 6, 2025
Agriculture is an essential foundation that supports numerous economies, and the longevity of the coffee business is of paramount significance. Controlling and safeguarding coffee farms from harmful pests, including the Coffee Berry Borer, Mealybugs,...
ESM-Ezy: a deep learning strategy for the mining of novel multicopper oxidases with superior properties.
Nature communications
Apr 6, 2025
The UniProt database is a valuable resource for biocatalyst discovery, yet predicting enzymatic functions remains challenging, especially for low-similarity sequences. Identifying superior enzymes with enhanced catalytic properties is even harder. To...
Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection.
Medical image analysis
Apr 5, 2025
Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imaging Trials (VITs) present a solution by simulating clinical trial components in a controlled, risk-f...
Parametric-MAA: fast, object-centric avoidance of metal artifacts for intraoperative CBCT.
International journal of computer assisted radiology and surgery
Apr 5, 2025
PURPOSE: Metal artifacts remain a persistent issue in intraoperative CBCT imaging. Particularly in orthopedic and trauma applications, these artifacts obstruct clinically relevant areas around the implant, reducing the modality's clinical value. Meta...
Open-source deep-learning models for segmentation of normal structures for prostatic and gynecological high-dose-rate brachytherapy: Comparison of architectures.
Journal of applied clinical medical physics
Apr 5, 2025
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...
Unsupervised brain MRI tumour segmentation via two-stage image synthesis.
Medical image analysis
Apr 5, 2025
Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real...
A novel deep learning-based floating garbage detection approach and its effectiveness evaluation in environmentally sustainable development.
Journal of environmental management
Apr 5, 2025
Floating garbage removal is an essential environmental strategy to reduce water pollution and achieve environmental sustainability, and it is a pressing issue for global ecological restoration. Under the interference of complex environments, floating...
Joint identification of hydraulic conductivity and groundwater pollution sources using unscented Kalman smoother with multiple data assimilation and deep learning.
Ecotoxicology and environmental safety
Apr 5, 2025
Identification of groundwater pollution sources (IGPSs) is a prerequisite for pollution remediation and pollution risk prediction. Data assimilation approaches have been used extensively in IGPSs field in recent years. A data assimilation approach-un...
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