James M. Balter

A preference‐integrated optimization system for medical physics shift scheduling

Benjamin S. Rosen, Zheng Zhang, Karolyn M. Hopfensperger, Kelly C. Paradis et autres

BACKGROUND: Clinical shift scheduling for medical physicists is challenging given multidisciplinary roles and competing clinical, research, and service demands. Manual workflows often lack the flexibility and transparency needed for this complex field. PURPOSE: To develop, deploy, and evaluate a preference-driven, optimization-based scheduling …

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Evaluation of volumetric breathing motion prediction of the stomach using dynamic golden-angle radial MRI

Robert J. Jones, Lianli Liu, Daekeun You, Jeffrey A. Fessler et autres

Abstract Objective . The motion of abdominal organs complicates accurate radiotherapy (RT) planning and delivery. Accurate short-term prediction of respiratory motion is essential for image-guided adaptive RT in the abdomen. This study evaluates the performance of a kernel ridge regression-based breathing motion …

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Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement

Lixuan Chen, Zhongnan Liu, Jesse Hamilton, James M. Balter et autres

Prospective reconstruction is crucial in many clinical applications such as MRI-guided radiotherapy, which demands accurate image reconstruction and fast motion estimation from currently acquired measurements. However, prospective reconstruction remains challenging due to ultra-sparse sampling and stringent latency requirements. In this work, we …

Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement

Lixuan Chen, Zhongnan Liu, Jesse Hamilton, James M. Balter et autres

Prospective reconstruction is crucial in many clinical applications such as MRI-guided radiotherapy, which demands accurate image reconstruction and fast motion estimation from currently acquired measurements. However, prospective reconstruction remains challenging due to ultra-sparse sampling and stringent latency requirements. In this work, we …

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Deep learning based 3D brain metastasis synthesis with configurable parameters for 3D data augmentation

Douglas S. Kondziolka, Yueh Lee, Mohannad M. Ibrahim, Jun Lian et autres

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Deep learning based 3D brain metastasis synthesis with configurable parameters for 3D data augmentation

Gengyan Zhao, Eli Gibson, Youngjin Yoo, Thomas Joseph Re et autres

To develop and evaluate deep learning methods for synthesizing 3D brain metastases (BM) on magnetic resonance (MR) images to improve downstream BM detection and segmentation performances for robust clinical detection and streamlined treatment-planning workflows, T1-weighted MR images of 1832 patients with 10,276 …

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Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion

Jorge Tapias Gomez, Nishant Nadkarni, Lando S Bosma, Jue Jiang et autres

Objective. Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging to implement for highly mobile gastrointestinal (GI) organs. To address this, patient-specific digital twins (DTs) modeling temporally varying motion were created …

Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion

Jorge Tapias Gomez, Nishant Nadkarni, Lando S Bosma, Jue Jiang et autres

Abstract Objective . Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging to implement for highly mobile gastrointestinal (GI) organs. To address this, patient-specific digital twins (DTs) modeling temporally varying motion …

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Artificial intelligence-based intrafraction motion monitoring for precise adaptive radiation therapy delivery

Lianli Liu, James M. Balter

Patient motion during treatment delivery results in discrepancies between the actual dose delivered and the planned dose distribution and is a significant source of radiation treatment uncertainty. Real-time adaptation of treatment delivery parameters based on changing patient anatomy has the potential to …

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Single-Spoke Motion-Compensated Dynamic 3D MRI Reconstruction via Neural Representation

Lixuan Chen, James M. Balter, Liyue Shen, Jeong Joon Park

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Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion

Jorge Tapias Gomez, Nishant Nadkarni, Lando S Bosma, Jue Jiang et autres

Objective: Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging to implement for highly mobile gastrointestinal (GI) organs. To address this, patient-specific digital twins (DT) modeling temporally varying motion were created …

Assessing the Relationship Between MR-Based Functional Dose Metrics and Post-Stereotactic Body Radiation Therapy Albumin-Bilirubin Change

Lise Wei, Madhava P. Aryal, John D. Rice, Joseph Evans et autres

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