AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 2101 to 2110 of 10288 articles

Decoupling visual and identity features for adversarial palm-vein image attack.

Neural networks : the official journal of the International Neural Network Society
Palm-vein has been widely used for biometric recognition due to its resistance to theft and forgery. However, with the emergence of adversarial attacks, most existing palm-vein recognition methods are vulnerable to adversarial image attacks, and to t...

Interactive Surgical Training in Neuroendoscopy: Real-Time Anatomical Feature Localization Using Natural Language Expressions.

IEEE transactions on bio-medical engineering
OBJECTIVE: This study addresses challenges in surgical education, particularly in neuroendoscopy, where the demand for optimized workflow conflicts with the need for trainees' active participation in surgeries. To overcome these challenges, we propos...

Joint [Formula: see text] and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: We present a model-based image reconstruction approach based on unrolled neural networks which corrects for image distortion and noise in low-field ( B  ∼  50 mT) MRI.

Comparison of Faster R-CNN, YOLO, and SSD for Third Molar Angle Detection in Dental Panoramic X-rays.

Sensors (Basel, Switzerland)
The use of artificial intelligence algorithms (AI) has gained importance for dental applications in recent years. Analyzing AI information from different sensor data such as images or panoramic radiographs (panoramic X-rays) can help to improve medic...

Deep learning-enabled fluorescence imaging for surgical guidance: training for oral cancer depth quantification.

Journal of biomedical optics
SIGNIFICANCE: Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth p...

Human lung cancer classification and comprehensive analysis using different machine learning techniques.

Microscopy research and technique
Lung cancer is the most common causes of death among all cancer-related diseases. A lung scan examination of the patient is the primary diagnostic technique. This scan analysis pertains to an MRI, CT, or X-ray. The automated classification of lung ca...

Automated diagnosis of atherosclerosis using multi-layer ensemble models and bio-inspired optimization in intravascular ultrasound imaging.

Medical & biological engineering & computing
Atherosclerosis causes heart disease by forming plaques in arterial walls. IVUS imaging provides a high-resolution cross-sectional view of coronary arteries and plaque morphology. Healthcare professionals diagnose and quantify atherosclerosis physica...

Two-step deep-learning identification of heel keypoints from video-recorded gait.

Medical & biological engineering & computing
Accurate and fast extraction of step parameters from video recordings of gait allows for richer information to be obtained from clinical tests such as Timed Up and Go. Current deep-learning methods are promising, but lack in accuracy for many clinica...

RSE-YOLOv8: An Algorithm for Underwater Biological Target Detection.

Sensors (Basel, Switzerland)
Underwater target detection is of great significance in underwater ecological assessment and resource development. To better protect the environment and optimize the development of underwater resources, we propose a new underwater target detection mo...

Leukemia detection and classification using computer-aided diagnosis system with falcon optimization algorithm and deep learning.

Scientific reports
Leukemia is a type of blood tumour that occurs because of abnormal enhancement in WBCs (white blood cells) in the bone marrow of the human body. Blood-forming tissue cancer influences the lymphatic and bone marrow system. The early diagnosis and dete...