AIMC Topic: Tomography, X-Ray Computed

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Differentiating novel coronavirus pneumonia from general pneumonia based on machine learning.

Biomedical engineering online
BACKGROUND: Chest CT screening as supplementary means is crucial in diagnosing novel coronavirus pneumonia (COVID-19) with high sensitivity and popularity. Machine learning was adept in discovering intricate structures from CT images and achieved exp...

Applications of Artificial Intelligence in Musculoskeletal Imaging: From the Request to the Report.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists should familiarize themselves with AI developments to become leaders in their clinical implementati...

Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain.

International journal of neural systems
Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and parallel computing model, combining the spiking and coupled mechanisms of neurons. This paper focuses on how to apply CNP systems to handle the fusion of multi-...

Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Currently, it is challenging to detect acute ischemic stroke (AIS)-related changes on computed tomography (CT) images. Therefore, we aimed to develop and evaluate an automatic AIS detection system involving a two-stage deep ...

Deep learning method for localization and segmentation of abdominal CT.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Computed Tomography (CT) imaging is widely used for studying body composition, i.e., the proportion of muscle and fat tissues with applications in areas such as nutrition or chemotherapy dose design. In particular, axial CT slices from the 3rd lumbar...

The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients.

European journal of nuclear medicine and molecular imaging
PURPOSE: This study aimed to investigate the deep learning model (DLM) combining computed tomography (CT) images and clinicopathological information for predicting anaplastic lymphoma kinase (ALK) fusion status in non-small cell lung cancer (NSCLC) p...

Machine Learning in Radiomic Renal Mass Characterization: Fundamentals, Applications, Challenges, and Future Directions.

AJR. American journal of roentgenology
The purpose of this study is to provide an overview of the traditional machine learning (ML)-based and deep learning-based radiomic approaches, with focus placed on renal mass characterization. ML currently has a very low barrier to entry into gene...