AIMC Topic: Deep Learning

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Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning.

Scientific reports
High-energy impacts, like vehicle crashes or falls, can lead to pelvic ring injuries. Rapid diagnosis and treatment are crucial due to the risks of severe bleeding and organ damage. Pelvic radiography promptly assesses fracture extent and location, b...

Computer-aided diagnosis for lung cancer using waterwheel plant algorithm with deep learning.

Scientific reports
Lung cancer (LC) is a life-threatening and dangerous disease all over the world. However, earlier diagnoses and treatment can save lives. Earlier diagnoses of malevolent cells in the lungs responsible for oxygenating the human body and expelling carb...

Deep learning approach for detecting tomato flowers and buds in greenhouses on 3P2R gantry robot.

Scientific reports
In recent years, significant advancements have been made in the field of smart greenhouses, particularly in the application of computer vision and robotics for pollinating flowers. Robotic pollination offers several benefits, including reduced labor ...

Skin cancer classification leveraging multi-directional compact convolutional neural network ensembles and gabor wavelets.

Scientific reports
Skin cancer (SC) is an important medical condition that necessitates prompt identification to ensure timely treatment. Although visual evaluation by dermatologists is considered the most reliable method, its efficacy is subjective and laborious. Deep...

Brain tumor image segmentation method using hybrid attention module and improved mask RCNN.

Scientific reports
To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this study introduces an enhanced instance segmentation method built upon mask region-based convolutional neural network. By incorporating squeeze-and-excitati...

Automated condylar seating assessment using a deep learning-based three-step approach.

Clinical oral investigations
OBJECTIVES: In orthognatic surgery, one of the primary determinants for reliable three-dimensional virtual surgery planning (3D VSP) and an accurate transfer of 3D VSP to the patient in the operation room is the condylar seating. Incorrectly seated c...

Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images.

IEEE transactions on medical imaging
Deep reinforcement learning (DRL) has demonstrated impressive performance in medical image segmentation, particularly for low-contrast and small medical objects. However, current DRL-based segmentation methods face limitations due to the optimization...

Deep-learning-based pyramid-transformer for localized porosity analysis of hot-press sintered ceramic paste.

PloS one
Scanning Electron Microscope (SEM) is a crucial tool for studying microstructures of ceramic materials. However, the current practice heavily relies on manual efforts to extract porosity from SEM images. To address this issue, we propose PSTNet (Pyra...

Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging.

The Journal of investigative dermatology
Hair quality is an important indicator of health in humans and other animals. Current approaches to assess hair quality are generally nonquantitative or are low throughput owing to technical limitations of splitting hairs. We developed a deep learnin...

Unlocking the potential of AI: Machine learning and deep learning models for predicting carcinogenicity of chemicals.

Journal of environmental science and health. Part C, Toxicology and carcinogenesis
The escalating apprehension surrounding the carcinogenic potential of chemicals emphasizes the imperative need for efficient methods of assessing carcinogenicity. Conventional experimental approaches such as in vitro and in vivo assays, albeit effect...