most citedKnowledge-based Radiation Treatment Planning: A Data-driven Method Survey

8 citations · 32 across the 8 of their papers we have counts for

collaborators

8 papers

physics.med-ph20208 cited

Knowledge-based Radiation Treatment Planning: A Data-driven Method Survey

Shadab Momin, Yabo Fu, Yang Lei +5

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 categor…

physics.med-ph2020

An institutional study on plan quality and variation of manual forward planning for Gamma Knife radiosurgery for vestibular schwannoma

Zhen Tian, Tonghe Wang, Xiaofeng Yang +5

Due to the complexity and cumbersomeness of Gamma Knife (GK) manual forward planning, the quality of the resulting treatment plans heavily depends on the planners skill, experience…

physics.med-ph2020

A plan quality control method of treatment planning for Gamma Knife radiosurgery

Tonghe Wang, Matt D. Giles, Elizabeth Butker +5

With many variables to adjust, conventional manual forward planning for Gamma Knife (GK) radiosurgery is very complicated and cumbersome. The resulting plan quality heavily depends…

eess.IV20205 cited

Deep Learning in Multi-organ Segmentation

Yang Lei, Yabo Fu, Tonghe Wang +4

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 met…

eess.IV20206 cited

Machine Learning in Quantitative PET Imaging

Tonghe Wang, Yang Lei, Yabo Fu +3

This paper reviewed the machine learning-based studies for quantitative positron emission tomography (PET). Specifically, we summarized the recent developments of machine learning-…

physics.med-ph20194 cited

Radiomics in Cancer Radiotherapy: a Review

Jiwoong Jeong, Arif Ali, Tian Liu +3

Radiomics is a nascent field in quantitative imaging that uses advanced algorithms and considerable computing power to describe tumor phenotypes, monitor treatment response, and as…