AIMC Topic: Image Processing, Computer-Assisted

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Reconstruction of multicontrast MR images through deep learning.

Medical physics
PURPOSE: Magnetic resonance (MR) imaging with a long scan time can lead to degraded images due to patient motion, patient discomfort, and increased costs. For these reasons, the role of rapid MR imaging is important. In this study, we propose the joi...

A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation.

Medical physics
PURPOSE: The purpose of this study is to develop a deep learning (DL) method for producing four-dimensional computed tomography (4DCT) ventilation imaging and to evaluate the accuracy of the DL-based ventilation imaging against single-photon emission...

Artificial Intelligence in the Evaluation of Body Composition.

Seminars in musculoskeletal radiology
Body composition entails the measurement of muscle and fat mass in the body and has been shown to impact clinical outcomes in various aspects of human health. As a result, the need is growing for reliable and efficient noninvasive tools to measure bo...

A Multi-Modal Person Perception Framework for Socially Interactive Mobile Service Robots.

Sensors (Basel, Switzerland)
In order to meet the increasing demands of mobile service robot applications, a dedicated perception module is an essential requirement for the interaction with users in real-world scenarios. In particular, multi sensor fusion and human re-identifica...

A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival.

Breast cancer research : BCR
BACKGROUND: Breast cancer intrinsic molecular subtype (IMS) as classified by the expression-based PAM50 assay is considered a strong prognostic feature, even when controlled for by standard clinicopathological features such as age, grade, and nodal s...

The Emerging Role of Radiomics in COPD and Lung Cancer.

Respiration; international review of thoracic diseases
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineab...

Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection.

Microscopy research and technique
Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and bleeding) through wireless capsule endoscopy (WCE) is still a key challenge. Doctors can identify these endoscopic diseases by using the computer-aided...

Convolutional neural network enhancement of fast-scan low-dose cone-beam CT images for head and neck radiotherapy.

Physics in medicine and biology
To improve image quality and CT number accuracy of fast-scan low-dose cone-beam computed tomography (CBCT) through a deep-learning convolutional neural network (CNN) methodology for head-and-neck (HN) radiotherapy. Fifty-five paired CBCT and CT image...

Person Re-Identification with Feature Pyramid Optimization and Gradual Background Suppression.

Neural networks : the official journal of the International Neural Network Society
Compared with face recognition, the performance of person re-identification (re-ID) is still far from practical application. Among various interferences, there are two factors seriously limiting the performance improvement, i.e., the feature discrimi...

Deep Learning-Based Single-Cell Optical Image Studies.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Optical imaging technology that has the advantages of high sensitivity and cost-effectiveness greatly promotes the progress of nondestructive single-cell studies. Complex cellular image analysis tasks such as three-dimensional reconstruction call for...