垄断 发表于 2025-3-25 05:35:02
http://reply.papertrans.cn/87/8676/867585/867585_21.png飞来飞去真休 发表于 2025-3-25 09:34:42
Synthesizing Realistic Brain MR Images with Noise Control,ribution of real MR images. Results show that the proposed method has comparable accuracy with the state-of-the-art approaches as measured by multiple similarity measurements while also being able to control the noise level in synthetic images. To further demonstrate the superiority of this model, w谁在削木头 发表于 2025-3-25 12:02:59
Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth,nerated a DWI UVIC by combining a patient-specific mathematical model of tumor growth with a multi-compartmental MRI signal equation. GBM growth was mathematically modeled using the Proliferation-Invasion-Hypoxia-Necrosis-Angiogenesis-Edema (PIHNA-E) model, which simulated tumor as being comprised oDetain 发表于 2025-3-25 18:45:23
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Heterogeneous Virtual Population of Simulated CMR Images for Improving the Generalization of Cardiaability in data, we vary acquisition parameters together with MR tissue properties to simulate diverse-looking images. The database includes 3240 CMR images of 30 male and 30 female subjects. To assess the usefulness of such data, we train a segmentation model with the simulated images and fine-tune躲债 发表于 2025-3-26 03:39:15
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A Gaussian Process Model Based Generative Framework for Data Augmentation of Multi-modal 3D Image V generative process for synthesising valid, realistic, and co-registered pairs of CT and MR 3D image volumes, 2) Evaluation of the consistency of the coupling between the generated image volume pairs. Our experiments show that the proposed method is a viable approach to data augmentation that could对待 发表于 2025-3-26 09:58:48
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http://reply.papertrans.cn/87/8676/867585/867585_29.pngtransdermal 发表于 2025-3-26 20:17:28
Image Synthesis as a Pretext for Unsupervised Histopathological Diagnosis,omain and demonstrate their superiority over currently used approaches on a challenging domain of digital pathology. Multifold improvement in image synthesis is demonstrated in terms of the quality and resolution of the generated images, validated also against the supervised model.