AIMC Topic: Tomography, X-Ray Computed

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Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Physics in medicine and biology
Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke (AIS) patients. The aim of this paper is to develop an automated segmentation method for accurately segmenting follow-up ischemic and hemorrhagic les...

Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images.

BioMed research international
Cross-modality medical image synthesis between magnetic resonance (MR) images and computed tomography (CT) images has attracted increasing attention in many medical imaging area. Many deep learning methods have been used to generate pseudo-MR/CT imag...

Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic functional region annotation of liver should be very useful for preoperative planning of liver resection in the clinical domain. However, many traditional computer-aided annotation methods based on anatomical landm...

Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...

Artificial intelligence CT screening model for thyroid-associated ophthalmopathy and tests under clinical conditions.

International journal of computer assisted radiology and surgery
PURPOSE: Thyroid-associated ophthalmopathy (TAO) might lead to blindness and orbital deformity. The early diagnosis and treatment are conducive to control disease progression, but currently, there is no effective screening method. The present study a...

Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography.

European journal of radiology
INTRODUCTION: Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and ...

Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
PURPOSE:  The aim of this study was to develop an algorithm for automated estimation of patient height and weight during computed tomography (CT) and to evaluate its accuracy in everyday clinical practice.

Performance of Prediction Models for Diagnosing Severe Aortic Stenosis Based on Aortic Valve Calcium on Cardiac Computed Tomography: Incorporation of Radiomics and Machine Learning.

Korean journal of radiology
OBJECTIVE: We aimed to develop a prediction model for diagnosing severe aortic stenosis (AS) using computed tomography (CT) radiomics features of aortic valve calcium (AVC) and machine learning (ML) algorithms.

The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia.

Scientific reports
To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-...

Convolutional neural network based proton stopping-power-ratio estimation with dual-energy CT: a feasibility study.

Physics in medicine and biology
Dual-energy computed tomography (DECT) has shown a great potential for lowering range uncertainties, which is necessary for truly leveraging the Bragg peak in proton therapy. However, analytical stopping-power-ratio (SPR) estimation methods have limi...