AIMC Topic: Image Processing, Computer-Assisted

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Delineation of clinical target volume and organs at risk in cervical cancer radiotherapy by deep learning networks.

Medical physics
PURPOSE: Delineation of the clinical target volume (CTV) and organs-at-risk (OARs) is important in cervical cancer radiotherapy. But it is generally labor-intensive, time-consuming, and subjective. This paper proposes a parallel-path attention fusion...

Deep learning for segmentation of the cervical cancer gross tumor volume on magnetic resonance imaging for brachytherapy.

Radiation oncology (London, England)
BACKGROUND: Segmentation of the Gross Tumor Volume (GTV) is a crucial step in the brachytherapy (BT) treatment planning workflow. Currently, radiation oncologists segment the GTV manually, which is time-consuming. The time pressure is particularly cr...

A Review Paper about Deep Learning for Medical Image Analysis.

Computational and mathematical methods in medicine
Medical imaging refers to the process of obtaining images of internal organs for therapeutic purposes such as discovering or studying diseases. The primary objective of medical image analysis is to improve the efficacy of clinical research and treatm...

Direct synthesis of multi-contrast brain MR images from MR multitasking spatial factors using deep learning.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning method to synthesize conventional contrast-weighted images in the brain from MR multitasking spatial factors.

Damage Detection and Localization of Bridge Deck Pavement Based on Deep Learning.

Sensors (Basel, Switzerland)
Bridge deck pavement damage has a significant effect on the driving safety and long-term durability of bridges. To achieve the damage detection and localization of bridge deck pavement, a three-stage detection method based on the you-only-look-once v...

Artificial intelligence applications in brachytherapy: A literature review.

Brachytherapy
PURPOSE: Artificial intelligence (AI) has the potential to simplify and optimize various steps of the brachytherapy workflow, and this literature review aims to provide an overview of the work done in this field.

Non-invasive grading of brain tumors using online support vector machine with dynamic fuzzy rule-based parameters optimization.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Non-invasive grading of brain tumors provides a valuable understanding of tumor growth that helps choose the proper treatment. In this paper, an online method with an innovative optimization approach as well as a new and fast tumor segmentation metho...

Evaluation of motion artefact reduction depending on the artefacts' directions in head MRI using conditional generative adversarial networks.

Scientific reports
Motion artefacts caused by the patient's body movements affect magnetic resonance imaging (MRI) accuracy. This study aimed to compare and evaluate the accuracy of motion artefacts correction using a conditional generative adversarial network (CGAN) w...

Decomposition of musculoskeletal structures from radiographs using an improved CycleGAN framework.

Scientific reports
This paper presents methods of decomposition of musculoskeletal structures from radiographs into multiple individual muscle and bone structures. While existing solutions require dual-energy scan for the training dataset and are mainly applied to stru...

Target-oriented deep learning-based image registration with individualized test-time adaptation.

Medical physics
BACKGROUND: A classic approach in medical image registration is to formulate an optimization problem based on the image pair of interest, and seek a deformation vector field (DVF) to minimize the corresponding objective, often iteratively. It has a c...