AIMC Topic: Tomography, X-Ray Computed

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Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation.

Medical physics
PURPOSE: We propose a deep learning method that classifies focal liver lesions (FLLs) into cysts, hemangiomas, and metastases from portal phase abdominal CT images. We propose a synthetic data augmentation process to alleviate the class imbalance and...

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.

Radiology
Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NL...

Fully automated unified prognosis of Covid-19 chest X-ray/CT scan images using Deep Covix-Net model.

Computers in biology and medicine
SARS-COV2 (Covid-19) prevails in the form of multiple mutant variants causing pandemic situations around the world. Thus, medical diagnosis is not accurate. Although several clinical diagnostic methodologies have been introduced hitherto, chest X-ray...

RCoNet: Deformable Mutual Information Maximization and High-Order Uncertainty-Aware Learning for Robust COVID-19 Detection.

IEEE transactions on neural networks and learning systems
The novel 2019 Coronavirus (COVID-19) infection has spread worldwide and is currently a major healthcare challenge around the world. Chest computed tomography (CT) and X-ray images have been well recognized to be two effective techniques for clinical...

Deep Learning-Based Computed Tomography Image Features in the Detection and Diagnosis of Perianal Abscess Tissue.

Journal of healthcare engineering
The performance characteristics of deep learning fully convolutional neural network (DLFCNN) algorithm-based computed tomography (CT) images were investigated in the detection and diagnosis of perianal abscess tissue. 60 patients who were medically d...

Scale- and Slice-aware Net (S aNet) for 3D segmentation of organs and musculoskeletal structures in pelvic MRI.

Magnetic resonance in medicine
PURPOSE: MRI of organs and musculoskeletal structures in the female pelvis presents a unique display of pelvic anatomy. Automated segmentation of pelvic structures plays an important role in personalized diagnosis and treatment on pelvic structures d...

[Importance of conventional pancreas imaging: ultrasound, CT, and MRI. Facts and possibilities].

Magyar onkologia
Modern imaging procedures, including CT and MR diagnostics, play a significant role in recognizing, characterizing, determining the extent of pancreatic tumor lesions, assessing their operability, and evaluating response to treatment and patient foll...

A deep-learning method using computed tomography scout images for estimating patient body weight.

Scientific reports
Body weight is an indispensable parameter for determination of contrast medium dose, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of computed tomography (CT...

Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients.

BMC medical informatics and decision making
BACKGROUND: In medical diagnosis and clinical practice, diagnosing a disease early is crucial for accurate treatment, lessening the stress on the healthcare system. In medical imaging research, image processing techniques tend to be vital in analyzin...

CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning-based reconstruction.

European radiology
OBJECTIVES: The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue phantom of fat, muscle and bone. Virtual monoenergetic images (VMI) by dual-energy measurements and...