2024年6月18日 · Eight applications of GANs in the head and neck region were summarized, including the classification of craniosynostosis, recognition of the presence of chronic sinusitis, diagnosis of radicular cysts in panoramic X-rays, segmentation of craniomaxillofacial bones, reconstruction of bone defects, removal of metal artifacts from CT scans ...

通过添加或修改 neck 和 head 的结构，可以轻松地将模型应用于不同的任务和数据集，从而提高模型的泛化能力和性能。 采用 backbone 、 neck 和 head 这种形式可以使 深度学习 模型更加灵活、可重用、易于训练和优化，同时也更易于扩展和应用于不同的任务。

2023年11月14日 · In this work, we developed a generative adversarial network (GAN)–based imaging model for the neck and abdomen that generates CT angiography (CTA)–like images from noncontrast CT images. In the quantitative image quality evaluation and visual quality evaluation, the synthetic CTA (Syn-CTA) images generated by the GAN-based CTA imaging model ...

2021年7月1日 · In this work, we proposed a Multi-Cycle GAN method for unpair head and neck MRI-to-CT synthesis. The experiment results in Table 1 demonstrate our superior performance. Especially, our model performs much better than Cycle GAN, where MAE improves from 0.0465 to 0.0416, ME from 0.0409 to 0.0340, PSNR from 37.1023 to 39.1053.

2024年9月1日 · In this paper, an adversarial training strategy is used in our deep learning network. This model is called the Multiple Organ Segmentation Generative Adversarial Network (MOS-GAN). The U-Net++ is our generator to create a multi-organ segmentation image by learning the end-to-end mapping from CT images to OARs segmentation.

2024年10月1日 · Intro: The current head-and-neck (HN) fluence map generator tends to produce highly modulated fluence maps and therefore high monitor units (MUs) for each beam, which leads to more delivery uncertainty and leakage dose. This project implements diffusion into the training process to mitigate this effect.

2022年3月9日 · Adaptive radiotherapy requires auto-segmentation in patients with head and neck (HN) cancer. In the current study, we propose an auto-segmentation model using a generative adversarial network (GAN) on magnetic resonance (MR) images of HN cancer for MR-guided radiotherapy (MRgRT).

2021年6月6日 · Background: We investigated the geometric and dosimetric impact of three-dimensional (3D) generative adversarial network (GAN)-based metal artifact reduction (MAR) algorithms on volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT) for the head and neck region, based on artifact-free computed tomography (CT ...

2024年3月14日 · Recently, increasing interest focused on generative adversarial network (GAN) and its variants, the GAN-based architecture has been demonstrated to synthesize high-quality sCT images with less blurriness compared with the CNN approaches [38,39,40,41,42,43,44].

2023年4月3日 · To improve the quality of CBCT for patients with head and neck cancer, a projection-domain CBCT correction method was proposed using a cycle-consistent generative adversarial network (cycle-GAN) and a nonlocal means filter (NLMF) based on a reference digitally reconstructed radiograph (DRR).