Zobrazeno 1 - 10
of 1 381
pro vyhledávání: '"Curran, Walter J."'
Autor:
Lin, Mingquan, Wynne, Jacob, Lei, Yang, Wang, Tonghe, Curran, Walter J., Liu, Tian, Yang, Xiaofeng
Medical imaging is widely used in cancer diagnosis and treatment, and artificial intelligence (AI) has achieved tremendous success in various tasks of medical image analysis. This paper reviews AI-based tumor subregion analysis in medical imaging. We
Externí odkaz:
http://arxiv.org/abs/2103.13588
This chapter reviews recent developments of generative adversarial networks (GAN)-based methods for medical and biomedical image synthesis tasks. These methods are classified into conditional GAN and Cycle-GAN according to the network architecture de
Externí odkaz:
http://arxiv.org/abs/2012.15446
Autor:
Dai, Xianjin, Lei, Yang, Wang, Tonghe, Dhabaan, Anees H., McDonald, Mark, Beitler, Jonathan J., Curran, Walter J., Zhou, Jun, Liu, Tian, Yang, Xiaofeng
Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated approach aided
Externí odkaz:
http://arxiv.org/abs/2010.04275
Autor:
Momin, Shadab, Fu, Yabo, Lei, Yang, Roper, Justin, Bradley, Jeffrey D., Curran, Walter J., Liu, Tian, Yang, Xiaofeng
This paper surveys the data-driven dose prediction approaches introduced for knowledge-based planning (KBP) in the last decade. These methods were classified into two major categories according to their methods and techniques of utilizing previous kn
Externí odkaz:
http://arxiv.org/abs/2009.07388
Autor:
Charyyev, Serdar, Wang, Tonghe, Lei, Yang, Ghavidel, Beth, Beitler, Jonathan J., McDonald, Mark, Curran, Walter J., Liu, Tian, Zhou, Jun, Yang, Xiaofeng
Purpose: Dual-energy CT (DECT) has been shown to derive stopping power ratio (SPR) map with higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. However, DECT is not as widely implemente
Externí odkaz:
http://arxiv.org/abs/2005.12908
Autor:
Lei, Yang, Tian, Zhen, Wang, Tonghe, Higgins, Kristin, Bradley, Jeffrey D., Curran, Walter J., Liu, Tian, Yang, Xiaofeng
Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-time volumetric images during the treatment delivery of lung stereotactic body radiation therapy (SBRT) for accurate and active motion management. In t
Externí odkaz:
http://arxiv.org/abs/2005.11832
Autor:
Dai, Xianjin, Lei, Yang, Liu, Yingzi, Wang, Tonghe, Ren, Lei, Curran, Walter J., Patel, Pretesh, Liu, Tian, Yang, Xiaofeng
Purpose: Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue type is a crucial issue for quantitative MRI image analysis in daily clinical practice. In this study, we present a deep learning-based approach
Externí odkaz:
http://arxiv.org/abs/2005.00516
This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning-based methods in inter- and intra-modality image synthesis by listing
Externí odkaz:
http://arxiv.org/abs/2004.10322
Autor:
Wang, Tonghe, Lei, Yang, Harms, Joseph, Ghavidel, Beth, Lin, Liyong, Beitler, Jonathan J., McDonald, Mark, Curran, Walter J., Liu, Tian, Zhou, Jun, Yang, Xiaofeng
Purpose: Dual-energy CT (DECT) has been used to derive relative stopping power (RSP) map by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of a
Externí odkaz:
http://arxiv.org/abs/2003.09058
Autor:
Lei, Yang, Fu, Yabo, Wang, Tonghe, Qiu, Richard L. J., Curran, Walter J., Liu, Tian, Yang, Xiaofeng
This paper presents a review of deep learning (DL) in multi-organ segmentation. We summarized the latest DL-based methods for medical image segmentation and applications. These methods were classified into six categories according to their network de
Externí odkaz:
http://arxiv.org/abs/2001.10619