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
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.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of applied clinical medical physics"
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
Extensive upfront validation and testing are needed prior to the clinical implementation of AI‐based auto‐segmentation tools
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.13873
Abstract: Artificial intelligence (AI) has emerged as a promising approach for automatic contouring in radiation therapy, compared to previous attempts, that is, image value thresholding, Atlas-based, and so forth. Results from a 2017 AAPM Grand Challenge… read more here.
Keywords: upfront validation; extensive upfront; auto segmentation; segmentation tools ... 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
Cascaded deep-learning based auto-segmentation for head and neck cancer patients: Organs at risk on T2 weighted magnetic resonance imaging.
Sign Up to like & getrecommendations! Published in 2021 at "Medical physics"
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
Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning.
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DOI: 10.1002/mp.15919
Abstract: BACKGROUND Routinely delineating of important skeletal growth centers is imperative to mitigate radiation-induced growth abnormalities for pediatric cancer patients treated with radiotherapy. However, it is hindered by several practical problems including difficult identification, time consumption… read more here.
Keywords: growth; growth centers; auto segmentation; tau net ... See more keywords
A novel specific grading standard study of auto-segmentation of organs at risk in thorax: subjective–objective-combined grading standard
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DOI: 10.1186/s12938-021-00890-8
Abstract: Background To develop a novel subjective–objective-combined (SOC) grading standard for auto-segmentation for each organ at risk (OAR) in the thorax. Methods A radiation oncologist manually delineated 13 thoracic OARs from computed tomography (CT) images of… read more here.
Keywords: grading standard; dsc; standard; auto segmentation ... See more keywords
Auto-segmentation and time-dependent systematic analysis of mesoscale cellular structure in β-cells during insulin secretion
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DOI: 10.1371/journal.pone.0265567
Abstract: The mesoscale description of the subcellular organization informs about cellular mechanisms in disease state. However, applications of soft X-ray tomography (SXT), an important approach for characterizing organelle organization, are limited by labor-intensive manual segmentation. Here… read more here.
Keywords: time; analysis; auto segmentation; systematic analysis ... See more keywords
Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation
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DOI: 10.3390/bioengineering10020181
Abstract: Deep-learning methods for auto-segmenting brain images either segment one slice of the image (2D), five consecutive slices of the image (2.5D), or an entire volume of the image (3D). Whether one approach is superior for… read more here.
Keywords: brain; auto; computational memory; auto segmentation ... See more keywords
A Novel and Automated Approach to Classify Radiation Induced Lung Tissue Damage on CT Scans
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DOI: 10.3390/cancers14051341
Abstract: Simple Summary Radiation-induced lung damage (RILD) is a common side effect of treating lung cancer with radiotherapy (RT). RILD is visible on CT imaging, and its radiological appearance can vary dramatically from patient to patient… read more here.
Keywords: class; auto segmentation; tissue; segmentation ... See more keywords