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   Articles with "segmentation" as a keyword



Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

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recommendations! Published in 2020 at "JAMA ophthalmology"

DOI: 10.1001/jamaophthalmol.2019.5983

Abstract: Importance Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage. Objective To develop a segmentation-free… read more here.

Keywords: glaucoma; segmentation; segmentation free; rnfl thickness ... See more keywords
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Technical note: Atlas‐based Auto‐segmentation of masticatory muscles for head and neck cancer radiotherapy

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recommendations! Published in 2020 at "Journal of Applied Clinical Medical Physics"

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
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A sensitivity analysis of probability maps in deep‐learning‐based anatomical segmentation

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recommendations! Published in 2021 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13331

Abstract: Abstract Purpose Deep‐learning‐based segmentation models implicitly learn to predict the presence of a structure based on its overall prominence in the training dataset. This phenomenon is observed and accounted for in deep‐learning applications such as… read more here.

Keywords: segmentation; anatomical segmentation; deep learning; learning based ... See more keywords

Attention‐guided duplex adversarial U‐net for pancreatic segmentation from computed tomography images

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recommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13537

Abstract: Abstract Purpose Segmenting the organs from computed tomography (CT) images is crucial to early diagnosis and treatment. Pancreas segmentation is especially challenging because the pancreas has a small volume and a large variation in shape.… read more here.

Keywords: computed tomography; guided duplex; attention guided; segmentation ... See more keywords

Comparison of Eclipse Smart Segmentation and MIM Atlas Segment for liver delineation for yttrium‐90 selective internal radiation therapy

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recommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13668

Abstract: Abstract Purpose The aim was to compare Smart Segmentation of Eclipse treatment planning system and Atlas Segment of MIM software for liver delineation for resin yttrium‐90 (Y‐90) procedures. Materials and methods CT images of 20… read more here.

Keywords: liver delineation; smart segmentation; mim; atlas segment ... See more keywords

Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network

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recommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13725

Abstract: Abstract Purpose Contouring clinical target volume (CTV) from medical images is an essential step for radiotherapy (RT) planning. Magnetic resonance imaging (MRI) is used as a standard imaging modality for CTV segmentation in cervical cancer… read more here.

Keywords: cervical cancer; volume; segmentation; ctv ... See more keywords

Fully automated breast segmentation on spiral breast computed tomography images

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recommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13726

Abstract: Abstract Introduction The quantification of the amount of the glandular tissue and breast density is important to assess breast cancer risk. Novel photon‐counting breast computed tomography (CT) technology has the potential to quantify them. For… read more here.

Keywords: segmentation; glandular tissue; breast; breast density ... See more keywords

Fully automatic tumor segmentation of breast ultrasound images with deep learning

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recommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.13863

Abstract: Abstract Background Breast ultrasound (BUS) imaging is one of the most prevalent approaches for the detection of breast cancers. Tumor segmentation of BUS images can facilitate doctors in localizing tumors and is a necessary step… read more here.

Keywords: breast ultrasound; fully automatic; tumor segmentation; bus ... See more keywords

DARU-Net: A dual attention residual U-Net for uterine fibroids segmentation on MRI.

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recommendations! Published in 2023 at "Journal of applied clinical medical physics"

DOI: 10.1002/acm2.13937

Abstract: Abstract Purpose Uterine fibroid is the most common benign tumor in female reproductive organs. In order to guide the treatment, it is crucial to detect the location, shape, and size of the tumor. This study… read more here.

Keywords: uterine fibroids; attention mechanisms; segmentation; deep learning ... See more keywords

Automatic end‐to‐end VMAT treatment planning for rectal cancers

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recommendations! Published in 2024 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.14259

Abstract: Abstract Background The treatment planning process from segmentation to producing a deliverable plan is time‐consuming and labor‐intensive. Existing solutions automate the segmentation and planning processes individually. The feasibility of combining auto‐segmentation and auto‐planning for volumetric… read more here.

Keywords: segmentation; end end; auto; bowel ... See more keywords

Evaluation and failure analysis of four commercial deep learning‐based autosegmentation software for abdominal organs at risk

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recommendations! Published in 2025 at "Journal of Applied Clinical Medical Physics"

DOI: 10.1002/acm2.70010

Abstract: Abstract Purpose Deep learning‐based segmentation of organs‐at‐risk (OAR) is emerging to become mainstream in clinical practice because of the superior performance over atlas and model‐based autocontouring methods. While several commercial deep learning‐based autosegmentation solutions are… read more here.

Keywords: deep learning; segmentation; autosegmentation; learning based ... See more keywords