AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.

Journal of computer assisted tomography
OBJECTIVE: The aim of this study was to assess the effectiveness of a deep learning-based image contrast-boosting algorithm by enhancing the image quality of low-dose computed tomography pulmonary angiography at reduced iodine load.

An anthropomorphic diagnosis system of pulmonary nodules using weak annotation-based deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The accurate categorization of lung nodules in CT scans is an essential aspect in the prompt detection and diagnosis of lung cancer. The categorization of grade and texture for nodules is particularly significant since it can aid radiologists and cli...

Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.

Scientific reports
The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improv...

Detection of breast cancer in digital breast tomosynthesis with vision transformers.

Scientific reports
Digital Breast Tomosynthesis (DBT) has revolutionized more traditional breast imaging through its three-dimensional (3D) visualization capability that significantly enhances lesion discernibility, reduces tissue overlap, and improves diagnostic preci...

Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles.

Journal of imaging informatics in medicine
Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)-based methods for registering the locations of lesions between the craniocaudal (CC) and mediolateral oblique (MLO) mammographic X-ray image views. M...

Deep learning-based reconstruction improves the image quality of low-dose CT enterography in patients with inflammatory bowel disease.

Abdominal radiology (New York)
PURPOSE: Lifelong re-examination of CT enterography (CTE) in patients with inflammatory bowel disease (IBD) may be necessary, and reducing radiation exposure during CT examinations is crucial. We investigated the potential application of deep learnin...