AIMC Topic: Tomography, X-Ray Computed

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Radiomics prediction of surgery in ulcerative colitis refractory to medical treatment.

Techniques in coloproctology
BACKGROUND: The surgeries in drug-resistant ulcerative colitis are determined by complex factors. This study evaluated the predictive performance of radiomics analysis on the basis of whether patients with ulcerative colitis in hospital were in the s...

[The computer-aided diagnosis model of middle ear cholesteatoma based on integrated convolutional neural networks].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional...

Artificial intelligence-based pulmonary vessel segmentation: an opportunity for automated three-dimensional planning of lung segmentectomy.

Interdisciplinary cardiovascular and thoracic surgery
OBJECTIVES: This study aimed to develop an automated method for pulmonary artery and vein segmentation in both left and right lungs from computed tomography (CT) images using artificial intelligence (AI). The segmentations were evaluated using PulmoS...

Artificial intelligence-based automated matching of pulmonary nodules on follow-up chest CT.

European radiology experimental
BACKGROUND: The growing demand for follow-up imaging highlights the need for tools supporting the assessment of pulmonary nodules over time. We evaluated the performance of an artificial intelligence (AI)-based system for automated nodule matching.

Accuracy of Low-Dose Chest CT-Based Artificial Intelligence Models in Osteoporosis Detection: A Systematic Review and Meta-analysis.

Calcified tissue international
The purpose of this study is to systematically review and evaluate the accuracy of low-dose chest CT-based artificial intelligence in osteoporosis screening. A systematic literature search for relevant studies up to 13th December 2024 was performed i...

Successful Application of Artificial Intelligence-Assisted Analysis of Invasive Pulmonary Adenocarcinoma Less Than 6 mm in Size: A Case Report and Literature Review.

The clinical respiratory journal
INTRODUCTION: Screening of lung nodules helps on early diagnosis of lung cancer, especially invasive pulmonary adenocarcinoma. Artificial intelligence (AI) has been applied in diagnosis of cancers. We used the AI-assisted lung nodule diagnostic syste...

Image-Based Deep Learning Model for Predicting Lymph Node Metastasis in Lung Adenocarcinoma With CT ≤ 2 cm.

Thoracic cancer
BACKGROUND: Lymph node metastasis (LNM) poses a considerable threat to survival in lung adenocarcinoma. Currently, minor resection is the recommended surgical approach for small-diameter lung cancer. The accurate preoperative identification of LNM in...

Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation.

Health technology assessment (Winchester, England)
BACKGROUND: Lung cancer is one of the most common types of cancer and the leading cause of cancer death in the United Kingdom. Artificial intelligence-based software has been developed to reduce the number of missed or misdiagnosed lung nodules on co...

Association of Deep Learning-based Chest CT-derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis.

Radiology
Background Forced vital capacity (FVC) is a standard measure of respiratory function in patients with amyotrophic lateral sclerosis (ALS) but has limitations, particularly for patients with bulbar impairment. Purpose To determine the value of deep le...

Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.

Nature communications
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative planning. Despite the promise of 3D reconstruction, clinical adoption remains limited due to time c...