AIMC Topic: Tomography, X-Ray Computed

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COVID-19 detection in CT and CXR images using deep learning models.

Biogerontology
Infectious diseases pose a threat to human life and could affect the whole world in a very short time. Corona-2019 virus disease (COVID-19) is an example of such harmful diseases. COVID-19 is a pandemic of an emerging infectious disease, called coron...

Diagnostic validation of a deep learning nodule detection algorithm in low-dose chest CT: determination of optimized dose thresholds in a virtual screening scenario.

European radiology
OBJECTIVES: This study was conducted to evaluate the effect of dose reduction on the performance of a deep learning (DL)-based computer-aided diagnosis (CAD) system regarding pulmonary nodule detection in a virtual screening scenario.

Multi-channel convolutional neural network architectures for thyroid cancer detection.

PloS one
Early detection of malignant thyroid nodules leading to patient-specific treatments can reduce morbidity and mortality rates. Currently, thyroid specialists use medical images to diagnose then follow the treatment protocols, which have limitations du...

Denoising of pediatric low dose abdominal CT using deep learning based algorithm.

PloS one
OBJECTIVES: To evaluate standard dose-like computed tomography (CT) images generated by a deep learning method, trained using unpaired low-dose CT (LDCT) and standard-dose CT (SDCT) images.

A CT Image-Based Virtual Sensing Method to Estimate Bone Drilling Force for Surgical Robots.

IEEE transactions on bio-medical engineering
OBJECTIVE: Current surgical robots face challenges to understand preoperative images like human surgeons, which hindering robots from making full use of preoperative information to operate stably and efficiently. We offer a method to estimate drillin...

Performance of a deep learning-based CT image denoising method: Generalizability over dose, reconstruction kernel, and slice thickness.

Medical physics
PURPOSE: Deep learning (DL) is rapidly finding applications in low-dose CT image denoising. While having the potential to improve the image quality (IQ) over the filtered back projection method (FBP) and produce images quickly, performance generaliza...

Deep Learning-Based Chest CT Image Features in Diagnosis of Lung Cancer.

Computational and mathematical methods in medicine
This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed with lung cancer by surgery or puncture in hospital were selected as the research subjects. The Mask ...

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Radiology
Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation dose. However, traditional image reconstruction methods are associated with image noise in low-dose ac...

TransDIR: Deformable imaging registration network based on transformer to improve the feature extraction ability.

Medical physics
PURPOSE: Imaging registration has a significant contribution to guide and support physicians in the process of decision-making for diagnosis, prognosis, and treatment. However, existing registration methods based on the convolutional neural network c...