AIMC Topic: Radiotherapy, Image-Guided
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Inter-fraction deformable image registration using unsupervised deep learning for CBCT-guided abdominal radiotherapy.
Physics in medicine and biology
Apr 13, 2023
. CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fractional anatomic changes, e.g. tumor shrinkage, and daily OAR variation t...
Ensemble learning and personalized training for the improvement of unsupervised deep learning-based synthetic CT reconstruction.
Medical physics
Dec 17, 2022
BACKGROUND: The growing adoption of magnetic resonance imaging (MRI)-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows have brought the technical challenge of synthetic computed tomography (sCT) reconstruction to the forefr...
Explainability and controllability of patient-specific deep learning with attention-based augmentation for markerless image-guided radiotherapy.
Medical physics
Nov 24, 2022
BACKGROUND: We reported the concept of patient-specific deep learning (DL) for real-time markerless tumor segmentation in image-guided radiotherapy (IGRT). The method was aimed to control the attention of convolutional neural networks (CNNs) by artif...
A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Sep 5, 2022
INTRODUCTION: This study aims to apply a conditional Generative Adversarial Network (cGAN) to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance (MR) images of the thorax.
Real time volumetric MRI for 3D motion tracking via geometry-informed deep learning.
Medical physics
Jul 6, 2022
PURPOSE: To develop a geometry-informed deep learning framework for volumetric MRI with sub-second acquisition time in support of 3D motion tracking, which is highly desirable for improved radiotherapy precision but hindered by the long image acquisi...
Multimodal image synthesis based on disentanglement representations of anatomical and modality specific features, learned using uncooperative relativistic GAN.
Medical image analysis
Jun 11, 2022
Growing number of methods for attenuation-coefficient map estimation from magnetic resonance (MR) images have recently been proposed because of the increasing interest in MR-guided radiotherapy and the introduction of positron emission tomography (PE...
A Prior Knowledge-Guided, Deep Learning-Based Semiautomatic Segmentation for Complex Anatomy on Magnetic Resonance Imaging.
International journal of radiation oncology, biology, physics
Jun 4, 2022
PURPOSE: Despite recent substantial improvement in autosegmentation using deep learning (DL) methods, labor-intensive and time-consuming slice-by-slice manual editing is often needed, particularly for complex anatomy (eg, abdominal organs). This work...
Tackling the class imbalance problem of deep learning-based head and neck organ segmentation.
International journal of computer assisted radiology and surgery
May 16, 2022
PURPOSE: The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image- guided radiation therapy. The automation of the segmentation task is therefore of high clinical relevance. Deep learning (DL)-based medi...
Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.
Radiation oncology (London, England)
Jan 31, 2022
BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric parameters might be more relevant in clinical practice but is often lacking in the literature. The aim of t...
Development of a deep learning-based patient-specific target contour prediction model for markerless tumor positioning.
Medical physics
Jan 27, 2022
PURPOSE: For pancreatic cancer patients, image guided radiation therapy and real-time tumor tracking (RTTT) techniques can deliver radiation to the target accurately. Currently, for the radiation therapy machine with kV X-ray imaging systems, interna...
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