AIMC Topic: Image Processing, Computer-Assisted

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Establishment and application of an artificial intelligence diagnosis system for pancreatic cancer with a faster region-based convolutional neural network.

Chinese medical journal
BACKGROUND: Early diagnosis and accurate staging are important to improve the cure rate and prognosis for pancreatic cancer. This study was performed to develop an automatic and accurate imaging processing technique system, allowing this system to re...

A future of automated image contouring with machine learning in radiation therapy.

Journal of medical radiation sciences
Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is al...

High Accuracy of Convolutional Neural Network for Evaluation of Helicobacter pylori Infection Based on Endoscopic Images: Preliminary Experience.

Clinical and translational gastroenterology
OBJECTIVES: Application of artificial intelligence in gastrointestinal endoscopy is increasing. The aim of the study was to examine the accuracy of convolutional neural network (CNN) using endoscopic images for evaluating Helicobacter pylori (H. pylo...

[Clinical application of convolutional neural network in pathological diagnosis of metastatic lymph nodes of gastric cancer].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To examine the value and clinical application of convolutional neural network in pathological diagnosis of metastatic lymph nodes of gastric cancer. Totally 124 patients with advanced gastric cancer who underwent radical gastrectomy plus D2 lymphad...

One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection.

Medical physics
PURPOSE: Computed tomography for the reconstruction of region of interest (ROI) has advantages in reducing the x-ray dose and the use of a small detector. However, standard analytic reconstruction methods such as filtered back projection (FBP) suffer...

Metal artifact reduction for practical dental computed tomography by improving interpolation-based reconstruction with deep learning.

Medical physics
PURPOSE: Metal artifact is a quite common problem in diagnostic dental computed tomography (CT) images. Due to the high attenuation of heavy materials such as metal, severe global artifacts can occur in reconstructions. Typical metal artifact reducti...

A two-dimensional feasibility study of deep learning-based feature detection and characterization directly from CT sinograms.

Medical physics
Machine Learning, especially deep learning, has been used in typical x-ray computed tomography (CT) applications, including image reconstruction, image enhancement, image domain feature detection and image domain feature characterization. To our know...

Motion-compensated frame rate up-conversion in carotid ultrasound images using optical flow and manifold learning.

Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir
OBJECTIVE: Carotid ultrasonography is a reliable and non-invasive method to evaluate atherosclerosis disease and its complications. B-mode cineloops are widely used to assess the severity of atherosclerosis and its progression; ho- wever, tracking ra...