State‐of‐the‐Art Report: Visual Computing in Radiation Therapy Planning

Schlachter, Matthias; Raidou, Renata Georgia; Muren, L.P.; Preim, Bernhard; Putora, Paul Martin; Bühler, Katja

doi:10.1111/cgf.13726

Cited by 10 publications

(7 citation statements)

References 172 publications

(252 reference statements)

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“…A prominent application of medical imaging for treatment planning is the determination of dose radiation. Schlachter et al [SRM∗19] highlighted the importance of uncertainty‐aware visualization in this application.…”

Section: Applicationsmentioning

confidence: 99%

Uncertainty‐aware Visualization in Medical Imaging ‐ A Survey

Gillmann

Saur

Wischgoll

et al. 2021

Computer Graphics Forum

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Medical imaging (image acquisition, image transformation, and image visualization) is a standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students. Each of these steps is affected by uncertainty, which can highly influence the decision‐making process of clinicians. Visualization can help in understanding and communicating these uncertainties. In this manuscript, we aim to summarize the current state‐of‐the‐art in uncertainty‐aware visualization in medical imaging. Our report is based on the steps involved in medical imaging as well as its applications. Requirements are formulated to examine the considered approaches. In addition, this manuscript shows which approaches can be combined to form uncertainty‐aware medical imaging pipelines. Based on our analysis, we are able to point to open problems in uncertainty‐aware medical imaging.

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Section: Applicationsmentioning

confidence: 99%

Uncertainty‐aware Visualization in Medical Imaging ‐ A Survey

Gillmann

Saur

Wischgoll

et al. 2021

Computer Graphics Forum

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“…For volume visualization, referred to as spatial visualization in the following, a number of reviews exist, and we refer the reader to most recent surveys on the matter. An overview of VC in RT can be found, e.g., in [34] and [33], and for domain independent multi-modality visualization in [21,27].…”

Section: Related Visualization Approachesmentioning

confidence: 99%

“…Radiation therapy (RT) is one of the major curative approaches for cancer [9], and has been used as cancer treatment for more than a century [36] undergoing a steady development in the past decade [38]. Despite the significant technological advancements of RT over the last decades, there are still many challenges to address [34].…”

Section: Introductionmentioning

confidence: 99%

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Exploration of Overlap Volumes for Radiotherapy Plan Evaluation with the Aim of Healthy Tissue Sparing

Schlachter¹,

Peters²,

Camenisch³

et al. 2021

Preprint

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Development of a novel interactive visualization approach for the exploration of radiotherapy treatment plans with a focus on overlap volumes with the aim of healthy tissue sparing. Methods:We propose a visualization approach to include overlap volumes in the radiotherapy treatment plan evaluation process. Quantitative properties can be interactively explored to identify critical regions and used to steer the visualization for a detailed inspection of candidates. We evaluated our approach with a user study covering the individual visualizations and their interactions regarding helpfulness, comprehensibility, intuitiveness, decision-making and speed.Results: A user study with three domain experts was conducted using our software and evaluating five data sets each representing a different type of cancer and location by performing a set of tasks and filling out a questionnaire. The results show that the visualizations and interactions help to identify and evaluate overlap volumes according to their physical and dose properties. Furthermore, the task of finding dose hots spots can also benefit from our approach. Conclusions:The results indicate the potential to enhance the current treatment plan evaluation process in terms of healthy tissue sparing.

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“…In this section, we indicate the most significant trends within medical visualization research that are applied to radiation oncology. The goal of this review is not to present a comprehensive state-of-the-art report, as this has been already performed by Schlachter et al [13]. Instead, we discuss selected principles of visualization in radiation oncology, in particular scientific visualization and visual analytics.…”

Section: Visualization Principles In Radiation Oncologymentioning

confidence: 99%

Principles of Visualization in Radiation Oncology

et al. 2020

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Background: Medical visualization employs elements from computer graphics to create meaningful, interactive visual representations of medical data, and it has become an influential field of research for many advanced applications like radiation oncology, among others. Visual representations employ the user's cognitive capabilities to support and accelerate diagnostic, planning, and quality assurance workflows based on involved patient data. Summary: This article discusses the basic underlying principles of visualization in the application domain of radiation oncology. The main visualization strategies, such as slice-based representations and surface and volume rendering are presented. Interaction topics, i.e., the combination of visualization and automated analysis methods, are also discussed. Key Messages: Slice-based representations are a common approach in radiation oncology, while volume visualization also has a longstanding history in the field. Perception within both representations can benefit further from advanced approaches, such as image fusion and multivolume or hybrid rendering. While traditional slice-based and volume representations keep evolving, the dimensionality and complexity of medical data are also increasing. To address this, visual analytics strategies are valuable, particularly for cohort or uncertainty visualization. Interactive visual analytics approaches represent a new opportunity to integrate knowledgeable experts and their cognitive abilities in exploratory processes which cannot be conducted by solely automatized methods.

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State‐of‐the‐Art Report: Visual Computing in Radiation Therapy Planning

Cited by 10 publications

References 172 publications

Uncertainty‐aware Visualization in Medical Imaging ‐ A Survey

Uncertainty‐aware Visualization in Medical Imaging ‐ A Survey

Exploration of Overlap Volumes for Radiotherapy Plan Evaluation with the Aim of Healthy Tissue Sparing

Principles of Visualization in Radiation Oncology

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