Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Bhalodia, Riddhish"'
Autor:
Sun, Keqiang, Jourabloo, Amin, Bhalodia, Riddhish, Meshry, Moustafa, Rong, Yu, Yang, Zhengyu, Nguyen-Phuoc, Thu, Haene, Christian, Xu, Jiu, Johnson, Sam, Li, Hongsheng, Bouaziz, Sofien
Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional methods for avatar creation often involve time-consuming scanning and r
Externí odkaz:
http://arxiv.org/abs/2408.13674
The manifold assumption for high-dimensional data assumes that the data is generated by varying a set of parameters obtained from a low-dimensional latent space. Deep generative models (DGMs) are widely used to learn data representations in an unsupe
Externí odkaz:
http://arxiv.org/abs/2205.13061
Statistical shape modeling is an essential tool for the quantitative analysis of anatomical populations. Point distribution models (PDMs) represent the anatomical surface via a dense set of correspondences, an intuitive and easy-to-use shape represen
Externí odkaz:
http://arxiv.org/abs/2201.03481
In current biological and medical research, statistical shape modeling (SSM) provides an essential framework for the characterization of anatomy/morphology. Such analysis is often driven by the identification of a relatively small number of geometric
Externí odkaz:
http://arxiv.org/abs/2111.07009
Autor:
Bhalodia, Riddhish, Elhabian, Shireen, Adams, Jadie, Tao, Wenzheng, Kavan, Ladislav, Whitaker, Ross
Statistical shape modeling (SSM) characterizes anatomical variations in a population of shapes generated from medical images. SSM requires consistent shape representation across samples in shape cohort. Establishing this representation entails a proc
Externí odkaz:
http://arxiv.org/abs/2110.07152
Autor:
Bhalodia, Riddhish, Hatamizadeh, Ali, Tam, Leo, Xu, Ziyue, Wang, Xiaosong, Turkbey, Evrim, Xu, Daguang
Localization and characterization of diseases like pneumonia are primary steps in a clinical pipeline, facilitating detailed clinical diagnosis and subsequent treatment planning. Additionally, such location annotated datasets can provide a pathway fo
Externí odkaz:
http://arxiv.org/abs/2110.03094
Autor:
Bhalodia, Riddhish, Elhabian, Shireen, Adams, Jadie, Tao, Wenzheng, Kavan, Ladislav, Whitaker, Ross
Publikováno v:
In Medical Image Analysis January 2024 91
Autor:
Tao, Wenzheng, Bhalodia, Riddhish, Anstadt, Erin, Kavan, Ladislav, Whitaker, Ross T., Goldstein, Jesse A.
This work describes an unsupervised method to objectively quantify the abnormality of general anatomical shapes. The severity of an anatomical deformity often serves as a determinant in the clinical management of patients. However, experiential bias
Externí odkaz:
http://arxiv.org/abs/2007.09307
Statistical shape modeling (SSM) has recently taken advantage of advances in deep learning to alleviate the need for a time-consuming and expert-driven workflow of anatomy segmentation, shape registration, and the optimization of population-level sha
Externí odkaz:
http://arxiv.org/abs/2007.06516
Statistical shape analysis is a very useful tool in a wide range of medical and biological applications. However, it typically relies on the ability to produce a relatively small number of features that can capture the relevant variability in a popul
Externí odkaz:
http://arxiv.org/abs/2006.07525