AIMC Topic: Tomography, X-Ray Computed

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Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT.

European radiology
OBJECTIVES: To develop an artificial intelligence (AI) system for predicting cervical lymph node metastasis (CLNM) preoperatively in patients with papillary thyroid cancer (PTC) based on CT images.

Performance and clinical applicability of machine learning in liver computed tomography imaging: a systematic review.

European radiology
OBJECTIVES: Machine learning (ML) for medical imaging is emerging for several organs and image modalities. Our objectives were to provide clinicians with an overview of this field by answering the following questions: (1) How is ML applied in liver c...

Robust and efficient abdominal CT segmentation using shape constrained multi-scale attention network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Although many deep learning-based abdominal multi-organ segmentation networks have been proposed, the various intensity distributions and organ shapes of the CT images from multi-center, multi-phase with various diseases introduce new challe...

Gender-specific data-driven adiposity subtypes using deep-learning-based abdominal CT segmentation.

Obesity (Silver Spring, Md.)
OBJECTIVE: The aim of this study was to quantify abdominal adiposity and generate data-driven adiposity subtypes with different diabetes risks.

Medical image super-resolution reconstruction algorithms based on deep learning: A survey.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: With the high-resolution (HR) requirements of medical images in clinical practice, super-resolution (SR) reconstruction algorithms based on low-resolution (LR) medical images have become a research hotspot. This type of meth...

Comprehensive dose evaluation of a Deep Learning based synthetic Computed Tomography algorithm for pelvic Magnetic Resonance-only radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Magnetic Resonance (MR)-only radiotherapy enables the use of MR without the uncertainty of MR-Computed Tomography (CT) registration. This requires a synthetic CT (sCT) for dose calculations, which can be facilitated by a novel...

Denoising diffusion probabilistic models for 3D medical image generation.

Scientific reports
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models have generated realistic images from textual input, as demonstrated by DALL-E 2, Imagen, and Stable Diffusion. However, their use in m...

2D medical image synthesis using transformer-based denoising diffusion probabilistic model.

Physics in medicine and biology
. Artificial intelligence (AI) methods have gained popularity in medical imaging research. The size and scope of the training image datasets needed for successful AI model deployment does not always have the desired scale. In this paper, we introduce...

Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy.

Physics in medicine and biology
. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve the quality of on-board cone beam CT (CBCT) images for dose calcul...