Technical note: Atlas‐based Auto‐segmentation of masticatory muscles for head and neck cancer radiotherapy
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DOI: 10.1002/acm2.13008
Abstract: Abstract Purpose The study aimed to use quantitative geometric and dosimetric metrics to assess the accuracy of atlas‐based auto‐segmentation of masticatory muscles (MMs) compared to manual drawn contours for head and neck cancer (HNC) radiotherapy… read more here.
Keywords: auto; segmentation; based auto; auto segmentation ... See more keywords
Methodological approach to create an atlas using a commercial auto‐contouring software
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DOI: 10.1002/acm2.13093
Abstract: Abstract Purpose The aim of this work was to establish a methodological approach for creation and optimization of an atlas for auto‐contouring, using the commercial software MIM MAESTRO (MIM Software Inc. Cleveland OH). Methods A… read more here.
Keywords: auto; methodological approach; using commercial; software ... See more keywords
Prospects for daily online adaptive radiotherapy via ethos for prostate cancer patients without nodal involvement using unedited CBCT auto‐segmentation
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DOI: 10.1002/acm2.13399
Abstract: Abstract Purpose Implementing new online adaptive radiation therapy technologies is challenging because extra clinical resources are required particularly expert contour review. Here, we provide the first assessment of Varian's Ethos™ adaptive platform for prostate cancer… read more here.
Keywords: auto; auto segmentation; online adaptive; prostate cancer ... See more keywords
Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.
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DOI: 10.1002/acm2.13470
Abstract: OBJECTIVES Because radiotherapy is indispensible for treating cervical cancer, it is critical to accurately and efficiently delineate the radiation targets. We evaluated a deep learning (DL)-based auto-segmentation algorithm for automatic contouring of clinical target volumes… read more here.
Keywords: auto; based auto; cervical cancer; auto segmentation ... See more keywords
Quantifying intrafractional gastric motion using auto-segmentation on MRI: Deformation and respiratory-induced displacement compared.
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DOI: 10.1002/acm2.13864
Abstract: BACKGROUND AND PURPOSE For accurate pre-operative gastric radiotherapy, intrafractional changes must be taken into account. The aim of this study is to quantify local gastric deformations and compare these deformations with respiratory-induced displacement. MATERIALS AND… read more here.
Keywords: sddeform; induced displacement; deformation; respiratory induced ... See more keywords
Resection cavity auto-contouring for patients with pediatric medulloblastoma using only CT information.
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DOI: 10.1002/acm2.13956
Abstract: PURPOSE Target delineation for radiation therapy is a time-consuming and complex task. Autocontouring gross tumor volumes (GTVs) has been shown to increase efficiency. However, there is limited literature on post-operative target delineation, particularly for CT-based… read more here.
Keywords: cavity auto; auto; pre selected; resection cavity ... See more keywords
Evaluation of Atlas‐based auto‐segmentation of liver in MR images for Yttrium‐90 selective internal radiation therapy
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DOI: 10.1002/acm2.13979
Abstract: Abstract Purpose The aim was to explore the feasibility of applying an atlas‐based auto‐segmentation tool, MIM Atlas Segment, for liver delineation in MR images in Y‐90 selective internal radiation therapy (SIRT). Materials and methods MR… read more here.
Keywords: liver; auto; auto segmentation; atlas based ... See more keywords
Induction with MEDA regimen and consolidation with Auto‐HSCT for stage IV NKTCL patients: A prospective multicenter study
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DOI: 10.1002/ijc.34055
Abstract: Optimal treatment strategies for natural killer/T‐cell lymphoma (NKTCL) patients with stage IV disease have not been well defined. In this prospective phase 2 study, we evaluated the treatment using MEDA (methotrexate, etoposide, dexamethasone and pegaspargase)… read more here.
Keywords: auto; auto hsct; nktcl patients; rate ... See more keywords
Fully automated treatment planning for MLC‐based robotic radiotherapy
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DOI: 10.1002/mp.14993
Abstract: Purpose To propose and validate a fully automated multicriterial treatment planning solution for a CyberKnife® equipped with an InCiseTM 2 multileaf collimator. Methods The AUTO BAO plans are generated using fully automated prioritized multicriterial optimization… read more here.
Keywords: auto; treatment planning; fully automated; auto bao ... See more keywords
Cascaded deep-learning based auto-segmentation for head and neck cancer patients: Organs at risk on T2 weighted magnetic resonance imaging.
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DOI: 10.1002/mp.15290
Abstract: PURPOSE To investigate multiple deep learning methods for automated segmentation (auto-segmentation) of the parotid glands, submandibular glands, level II and level III lymph nodes on magnetic resonance imaging (MRI). Outlining radiosensitive organs on images used… read more here.
Keywords: auto; submandibular glands; segmentation; deep learning ... See more keywords
A pair of deep learning auto-contouring models for prostate cancer patients injected with a radio-transparent versus radiopaque hydrogel spacer.
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DOI: 10.1002/mp.16375
Abstract: BACKGROUND Absorbable hydrogel spacer injected between prostate and rectum is gaining popularity for rectal sparing. The spacer alters patient anatomy and thus requires new auto-contouring models. PURPOSE To report the development and comprehensive evaluation of… read more here.
Keywords: prostate; auto; bladder rectum; spacer ... See more keywords