AIMC Topic: Tomography, X-Ray Computed

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A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy.

Physics in medicine and biology
. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical ...

Artificial intelligence-powered software detected more than half of the liver metastases overlooked by radiologists on contrast-enhanced CT.

European journal of radiology
PURPOSE: To evaluate the sensitivity of artificial intelligence (AI)-powered software in detecting liver metastases, especially those overlooked by radiologists.

How will artificial intelligence transform cardiovascular computed tomography? A conversation with an AI model.

Journal of cardiovascular computed tomography
Artificial intelligence (AI) has the potential to transform healthcare, but its clinical use also has important challenges and limitations. Recently natural language processing and generative pre-training transformer (GPT) models have gained particul...

Fully-automated detection of small bowel carcinoid tumors in CT scans using deep learning.

Medical physics
BACKGROUND: Small bowel carcinoid tumor is a rare neoplasm and increasing in incidence. Patients with small bowel carcinoid tumors often experience long delays in diagnosis due to the vague symptoms, slow growth of tumors, and lack of clinician aware...

[Update: Small bowel diseases in computed tomography and magnetic resonance imaging].

Radiologie (Heidelberg, Germany)
CLINICAL/METHODICAL ISSUE: Radiological procedures play a crucial role in the diagnosis of small bowel disease. Due to a broad and quite nonspecific spectrum of symptoms, clinical evaluation is often difficult, and endoscopic procedures require signi...

An attention-based deep convolutional neural network for ultra-sparse-view CT reconstruction.

Computers in biology and medicine
X-ray Computed Tomography (CT) techniques play a vitally important role in clinical diagnosis, but radioactivity exposure can also induce the risk of cancer for patients. Sparse-view CT reduces the impact of radioactivity on the human body through sp...

MLF-IOSC: Multi-Level Fusion Network With Independent Operation Search Cell for Low-Dose CT Denoising.

IEEE transactions on medical imaging
Computed tomography (CT) is widely used in clinical medicine, and low-dose CT (LDCT) has become popular to reduce potential patient harm during CT acquisition. However, LDCT aggravates the problem of noise and artifacts in CT images, increasing diagn...

Report on the AAPM deep-learning spectral CT Grand Challenge.

Medical physics
BACKGROUND: This Special Report summarizes the 2022 AAPM Grand Challenge on Deep-Learning spectral Computed Tomography (DL-spectral CT) image reconstruction.

A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

Medical physics
BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regional lung ventilation with exceptional detail within a single breath. However, this modality requires specialized equipment and exogenous contrast, wh...