AIMC Topic: Tomography, X-Ray Computed

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A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans.

NeuroImage. Clinical
Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency medical attention, which is routinely diagnosed using non-contrast head CT imaging. The diagnostic accuracy of acute ICH on CT varies greatly among radiologists...

Diagnostic performance and image quality of deep learning image reconstruction (DLIR) on unenhanced low-dose abdominal CT for urolithiasis.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Patients with urolithiasis undergo radiation overexposure from computed tomography (CT) scans. Improvement of image reconstruction is necessary for radiation dose reduction.

Transparent Machine Learning Models to Diagnose Suspicious Thoracic Lesions Leveraging CT Guided Biopsy Data.

Academic radiology
RATIONALE AND OBJECTIVES: To train and validate machine learning models capable of classifying suspicious thoracic lesions as benign or malignant and to further classify malignant lesions by pathologic subtype while quantifying feature importance for...

Diagnostic performance of deep learning models for detecting bone metastasis on whole-body bone scan in prostate cancer.

European journal of nuclear medicine and molecular imaging
PURPOSE: We evaluated the performance of deep learning classifiers for bone scans of prostate cancer patients.

An approach to the classification of COVID-19 based on CT scans using convolutional features and genetic algorithms.

Computers in biology and medicine
COVID-19 is a respiratory disease that, as of July 15th, 2021, has infected more than 187 million people worldwide and is responsible for more than 4 million deaths. An accurate diagnosis of COVID-19 is essential for the treatment and control of the ...

Deep Bidirectional Classification Model for COVID-19 Disease Infected Patients.

IEEE/ACM transactions on computational biology and bioinformatics
In December of 2019, a novel coronavirus (COVID-19) appeared in Wuhan city, China and has been reported in many countries with millions of people infected within only four months. Chest computed Tomography (CT) has proven to be a useful supplement to...

Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning.

Computers in biology and medicine
When doctors use contrast-enhanced computed tomography (CECT) images to predict the metastasis of axillary lymph nodes (ALN) for breast cancer patients, the prediction performance could be degraded by subjective factors such as experience, psychologi...

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

Journal of healthcare engineering
This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, studies its ability to distinguish benign and malignant thyroid lesions, and seeks ways to improve the accuracy of diagnosis. The normal control group se...

Automatic segmentation of lung tumors on CT images based on a 2D & 3D hybrid convolutional neural network.

The British journal of radiology
OBJECTIVE: A stable and accurate automatic tumor delineation method has been developed to facilitate the intelligent design of lung cancer radiotherapy process. The purpose of this paper is to introduce an automatic tumor segmentation network for lun...