Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Yeganeh, Yousef"'
Autor:
Yeganeh, Yousef, Lazuardi, Rachmadio, Shamseddin, Amir, Dari, Emine, Thirani, Yash, Navab, Nassir, Farshad, Azade
Surgical data science (SDS) is a field that analyzes patient data before, during, and after surgery to improve surgical outcomes and skills. However, surgical data is scarce, heterogeneous, and complex, which limits the applicability of existing mach
Externí odkaz:
http://arxiv.org/abs/2410.17751
Recent advances in generative models for medical imaging have shown promise in representing multiple modalities. However, the variability in modality availability across datasets limits the general applicability of the synthetic data they produce. To
Externí odkaz:
http://arxiv.org/abs/2409.13532
Scene graphs have emerged as accurate descriptive priors for image generation and manipulation tasks, however, their complexity and diversity of the shapes and relations of objects in data make it challenging to incorporate them into the models and g
Externí odkaz:
http://arxiv.org/abs/2311.02247
Autor:
Astaraki, Mehdi, De Benetti, Francesca, Yeganeh, Yousef, Toma-Dasu, Iuliana, Smedby, Örjan, Wang, Chunliang, Navab, Nassir, Wendler, Thomas
Robust and accurate detection and segmentation of heterogenous tumors appearing in different anatomical organs with supervised methods require large-scale labeled datasets covering all possible types of diseases. Due to the unavailability of such ric
Externí odkaz:
http://arxiv.org/abs/2305.12358
Autor:
Yeganeh, Yousef, Farshad, Azade, Guevercin, Goktug, Abu-zer, Amr, Xiao, Rui, Tang, Yongjian, Adeli, Ehsan, Navab, Nassir
Although the preservation of shape continuity and physiological anatomy is a natural assumption in the segmentation of medical images, it is often neglected by deep learning methods that mostly aim for the statistical modeling of input data as pixels
Externí odkaz:
http://arxiv.org/abs/2304.14572
Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and high-quality ima
Externí odkaz:
http://arxiv.org/abs/2304.14573
Autor:
Yeganeh, Yousef, Farshad, Azade, Weinberger, Peter, Ahmadi, Seyed-Ahmad, Adeli, Ehsan, Navab, Nassir
Although purely transformer-based architectures showed promising performance in many computer vision tasks, many hybrid models consisting of CNN and transformer blocks are introduced to fit more specialized tasks. Nevertheless, despite the performanc
Externí odkaz:
http://arxiv.org/abs/2304.14571
Graph representation of objects and their relations in a scene, known as a scene graph, provides a precise and discernible interface to manipulate a scene by modifying the nodes or the edges in the graph. Although existing works have shown promising
Externí odkaz:
http://arxiv.org/abs/2211.05499
Inpainting has recently been proposed as a successful deep learning technique for unsupervised medical image model discovery. The masks used for inpainting are generally independent of the dataset and are not tailored to perform on different given cl
Externí odkaz:
http://arxiv.org/abs/2207.05787
Autor:
Yeganeh, Yousef, Farshad, Azade, Boschmann, Johann, Gaus, Richard, Frantzen, Maximilian, Navab, Nassir
Federated learning (FL) is a distributed learning method that offers medical institutes the prospect of collaboration in a global model while preserving the privacy of their patients. Although most medical centers conduct similar medical imaging task
Externí odkaz:
http://arxiv.org/abs/2207.03448