AIMC Topic: Tomography, X-Ray Computed

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A learning-based material decomposition pipeline for multi-energy x-ray imaging.

Medical physics
PURPOSE: Benefiting from multi-energy x-ray imaging technology, material decomposition facilitates the characterization of different materials in x-ray imaging. However, the performance of material decomposition is limited by the accuracy of the deco...

Knowledge-based dose prediction models for head and neck cancer are strongly affected by interorgan dependency and dataset inconsistency.

Medical physics
PURPOSE: The goal of this study was to generate a large treatment plan database for head and neck (H&N) cancer patients that can be considered as the gold standard to train and validate models for knowledge-based (KB) treatment planning and QA. With ...

Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Thrombus characteristics identified on non-contrast CT (NCCT) are potentially associated with recanalization with intravenous (IV) alteplase in patients with acute ischemic stroke (AIS). Our aim was to determine the best radio...

Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network.

Medical image analysis
Synthesized medical images have several important applications. For instance, they can be used as an intermedium in cross-modality image registration or used as augmented training samples to boost the generalization capability of a classifier. In thi...

Swall-E: A robotic in-vitro simulation of human swallowing.

PloS one
Swallowing is a complex physiological function that can be studied through medical imagery techniques such as videofluoroscopy (VFS), dynamic magnetic resonance imagery (MRI) and fiberoptic endoscopic evaluation of swallowing (FEES). VFS is the gold ...

Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.

AJR. American journal of roentgenology
OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagnosis of thyroid cancer, it has the shortcomings of substantial radiation exposure and the use of contrast material (CM). The purpose of this article i...

AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.

Medical physics
PURPOSE: Radiation therapy (RT) is a common treatment option for head and neck (HaN) cancer. An important step involved in RT planning is the delineation of organs-at-risks (OARs) based on HaN computed tomography (CT). However, manually delineating O...

CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm.

Artificial intelligence in medicine
Liver tumor segmentation from computed tomography (CT) images is a critical and challenging task. Due to the fuzziness in the liver pixel range, the neighboring organs of the liver with the same intensity, high noise and large variance of tumors. The...