AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 8381 to 8390 of 10288 articles

Salient object detection based on multi-scale contrast.

Neural networks : the official journal of the International Neural Network Society
Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object de...

Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models.

Computational intelligence and neuroscience
Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly suscept...

Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT.

IEEE transactions on medical imaging
Epicardial adipose tissue (EAT) is a visceral fat deposit related to coronary artery disease. Fully automated quantification of EAT volume in clinical routine could be a timesaving and reliable tool for cardiovascular risk assessment. We propose a ne...

Automated detection of preserved photoreceptor on optical coherence tomography in choroideremia based on machine learning.

Journal of biophotonics
Optical coherence tomography (OCT) can demonstrate early deterioration of the photoreceptor integrity caused by inherited retinal degeneration diseases (IRDs). A machine learning method based on random forests was developed to automatically detect co...

Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network.

Computers in biology and medicine
Stereotactic treatments are today the reference techniques for the irradiation of brain metastases in radiotherapy. The dose per fraction is very high, and delivered in small volumes (diameter <1 cm). As part of these treatments, effective detection ...

Self-learning computers for surgical planning and prediction of postoperative alignment.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: In past decades, the role of sagittal alignment has been widely demonstrated in the setting of spinal conditions. As several parameters can be affected, identifying the driver of the deformity is the cornerstone of a successful treatment app...

EmotionMeter: A Multimodal Framework for Recognizing Human Emotions.

IEEE transactions on cybernetics
In this paper, we present a multimodal emotion recognition framework called EmotionMeter that combines brain waves and eye movements. To increase the feasibility and wearability of EmotionMeter in real-world applications, we design a six-electrode pl...

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
BACKGROUND: Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, ...

Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...