In-Situ
发表于 2025-3-28 18:30:00
Deriving Lung Perfusion Directly from CT Image Using Deep Convolutional Neural Network: A Preliminal imaging suffers from many shortcomings, including the need of exogenous contrasts, longer processing time, etc. In this study, we present a new approach to derive the lung functional images, using a deep convolutional neural network to learn and exploit the underlying functional information in the
Obstacle
发表于 2025-3-28 19:10:58
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Immunotherapy
发表于 2025-3-29 00:00:21
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招致
发表于 2025-3-29 04:57:03
Dose Distribution Prediction for Optimal Treamtment of Modern External Beam Radiation Therapy for Nper proposes a new automatic method for predicting of dose distribution of Nasopharyngeal carcinoma (NPC) from contoured computer tomography (CT) images. The proposed method consists of two phases: (1) predicting the 2D optimal dose images of each beam from contoured CT images of a patient by convol
Hla461
发表于 2025-3-29 09:11:35
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完全
发表于 2025-3-29 14:17:01
UC-GAN for MR to CT Image Synthesis,rsarial network (CycleGAN) is becoming an influential method, however, its image quality of synthesis is not optimal yet. In this study, we proposed a new learning method named U-Net-CycleGAN (UC-GAN) to generate synthetic CT (sCT) image for MRI-only radiation treatment planning, which integrated an
perpetual
发表于 2025-3-29 16:57:07
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粉笔
发表于 2025-3-29 20:35:36
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abreast
发表于 2025-3-30 02:50:46
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dysphagia
发表于 2025-3-30 05:56:12
https://doi.org/10.1057/978-1-137-46178-0e investigate the feasibility of CT-only dose prediction and the profitability of additional isocenter and contour information. To evaluate the network’s performance, a 5-fold cross-validation is performed on 79 prostate patients, all treated with volumetric modulated arc therapy.