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Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment and surgical planning. Recent advances of convolutional networks have demonstrated higher accuracy than…

计算机视觉与模式识别 · 计算机科学 2019-09-25 Ling Zhang , Le Lu , Xiaosong Wang , Robert M. Zhu , Mohammadhadi Bagheri , Ronald M. Summers , Jianhua Yao

Adaptive radiotherapy is a growing field of study in cancer treatment due to it's objective in sparing healthy tissue. The standard of care in several institutions includes longitudinal cone-beam computed tomography (CBCT) acquisitions to…

计算机视觉与模式识别 · 计算机科学 2023-03-08 William Trung Le , Chulmin Bang , Philippine Cordelle , Daniel Markel , Phuc Felix Nguyen-Tan , Houda Bahig , Samuel Kadoury

Background: Voxel-based analysis (VBA) for population level radiotherapy (RT) outcomes modeling requires topology preserving inter-patient deformable image registration (DIR) that preserves tumors on moving images while avoiding unrealistic…

图像与视频处理 · 电气工程与系统科学 2024-11-28 Jue Jiang , Chloe Min Seo Choi , Maria Thor , Joseph O. Deasy , Harini Veeraraghavan

In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. Motion models can be used to simulate motion patterns and assess anatomical robustness before delivery.…

Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The visibility of the tumor in kV images is limited since the…

计算机视觉与模式识别 · 计算机科学 2023-10-19 Yuzhen Ding , Hongying Feng , Yunze Yang , Jason Holmes , Zhengliang Liu , David Liu , William W. Wong , Nathan Y. Yu , Terence T. Sio , Steven E. Schild , Baoxin Li , Wei Liu

In current clinical practice, noisy and artifact-ridden weekly cone-beam computed tomography (CBCT) images are only used for patient setup during radiotherapy. Treatment planning is done once at the beginning of the treatment using…

图像与视频处理 · 电气工程与系统科学 2022-01-02 Navdeep Dahiya , Sadegh R Alam , Pengpeng Zhang , Si-Yuan Zhang , Anthony Yezzi , Saad Nadeem

Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manual time consuming delineation of radio-sensitive organs at…

Background and purpose: The delineation of the gross tumor volume (GTV) is a critical step for radiation therapy treatment planning. The delineation procedure is typically performed manually which exposes two major issues: cost and…

CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fractional anatomic changes. The purpose of this study is to propose…

图像与视频处理 · 电气工程与系统科学 2023-04-26 Huiqiao Xie , Yang Lei , Yabo Fu , Tonghe Wang , Justin Roper , Jeffrey D. Bradley , Pretesh Patel , Tian Liu , Xiaofeng Yang

Radiotherapy (RT) is a critical cancer treatment, with volumetric modulated arc therapy (VMAT) being a commonly used technique that enhances dose conformity by dynamically adjusting multileaf collimator (MLC) positions and monitor units…

医学物理 · 物理学 2025-06-26 Stefanos Achlatis , Efstratios Gavves , Jan-Jakob Sonke

Automatic segmentation of organs-at-risk (OAR) in computed tomography (CT) is an essential part of planning effective treatment strategies to combat lung and esophageal cancer. Accurate segmentation of organs surrounding tumours helps…

计算机视觉与模式识别 · 计算机科学 2019-05-21 Sulaiman Vesal , Nishant Ravikumar , Andreas Maier

Accurate segmentation of gross tumor volume (GTV) is essential for effective MRI-guided adaptive radiotherapy (MRgART) in head and neck cancer. However, manual segmentation of the GTV over the course of therapy is time-consuming and prone…

图像与视频处理 · 电气工程与系统科学 2024-12-03 Xin Tie , Weijie Chen , Zachary Huemann , Brayden Schott , Nuohao Liu , Tyler J. Bradshaw

Proton therapy offers superior organ-at-risk sparing but is highly sensitive to anatomical changes, making accurate deformable image registration (DIR) across longitudinal CT scans essential. Conventional DIR methods are often too slow for…

In adaptive radiotherapy, deformable image registration is often conducted between the planning CT and treatment CT (or cone beam CT) to generate a deformation vector field (DVF) for dose accumulation and contour propagation. The auto…

医学物理 · 物理学 2015-06-12 Xuejun Gu , Bin Dong , Jing Wang , John Yordy , Loren Mell , Xun Jia , Steve B. Jiang

Vestibular schwannomas (VS) are benign tumors that are generally managed by active surveillance with MRI examination. To further assist clinical decision-making and avoid overtreatment, an accurate prediction of tumor growth based on…

图像与视频处理 · 电气工程与系统科学 2024-04-05 Yunjie Chen , Jelmer M. Wolterink , Olaf M. Neve , Stephan R. Romeijn , Berit M. Verbist , Erik F. Hensen , Qian Tao , Marius Staring

Purpose: To develop an algorithm for real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image for lung cancer radiotherapy. Methods: Given a set of volumetric images of a patient at N…

医学物理 · 物理学 2015-05-18 Ruijiang Li , Xun Jia , John H. Lewis , Xuejun Gu , Michael Folkerts , Chunhua Men , Steve B. Jiang

Modeling of respiratory motion is important for a more accurate understanding and accounting of its effect on dose to cancers in the thorax and abdomen by radiotherapy. We have developed a model of respiration-induced organ motion in the…

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…

Clinical target volume (CTV) delineation from radiotherapy computed tomography (RTCT) images is used to define the treatment areas containing the gross tumor volume (GTV) and/or sub-clinical malignant disease for radiotherapy (RT). High…

图像与视频处理 · 电气工程与系统科学 2019-09-09 Dakai Jin , Dazhou Guo , Tsung-Ying Ho , Adam P. Harrison , Jing Xiao , Chen-kan Tseng , Le Lu

This work aims to generate realistic anatomical deformations from static patient scans. Specifically, we present a method to generate these deformations/augmentations via deep learning driven respiratory motion simulation that provides the…

计算机视觉与模式识别 · 计算机科学 2023-01-30 Donghoon Lee , Ellen Yorke , Masoud Zarepisheh , Saad Nadeem , Yu-Chi Hu
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