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   Articles with "segmentation methods" as a keyword



Comparative assessment of established and deep learning‐based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis

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recommendations! Published in 2024 at "NMR in Biomedicine"

DOI: 10.1002/nbm.5169

Abstract: In this study, our objective was to assess the performance of two deep learning‐based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two… read more here.

Keywords: deep learning; hippocampal volume; segmentation; learning based ... See more keywords

White blood cell (WBC) counting analysis in blood smear images using various color segmentation methods

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recommendations! Published in 2018 at "Measurement"

DOI: 10.1016/j.measurement.2017.11.002

Abstract: Abstract White blood cells (WBCs) is closely related to human immunity system which is useful to fight viruses and bacteria. Cancer therapy effectiveness and some of the blood-related diseases can be determined from the count… read more here.

Keywords: color; white blood; wbc counting; blood ... See more keywords

A comparison of accurate automatic hippocampal segmentation methods

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recommendations! Published in 2017 at "NeuroImage"

DOI: 10.1016/j.neuroimage.2017.04.018

Abstract: ABSTRACT The hippocampus is one of the first brain structures affected by Alzheimer's disease (AD). While many automatic methods for hippocampal segmentation exist, few studies have compared them on the same data. In this study,… read more here.

Keywords: hippocampal segmentation; segmentation; error correction; accurate automatic ... See more keywords

Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region

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recommendations! Published in 2018 at "Physics in Medicine and Biology"

DOI: 10.1088/1361-6560/aacb65

Abstract: Abstract Owing to its excellent soft-tissue contrast, magnetic resonance (MR) imaging has found an increased application in radiation therapy (RT). By harnessing these properties for treatment planning, automated segmentation methods can alleviate the manual workload… read more here.

Keywords: geometric dosimetric; treatment planning; segmentation; treatment ... See more keywords

A State-of-the-Art Survey for Microorganism Image Segmentation Methods and Future Potential

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2930111

Abstract: Microorganisms play a great role in ecosystem, wastewater treatment, monitoring of environmental changes, and decomposition of waste materials. However, some of them are harmful to humans and animals such as tuberculosis bacteria and plasmodium. In… read more here.

Keywords: image segmentation; segmentation methods; image; segmentation ... See more keywords

A Survey of Deep Learning for Retinal Blood Vessel Segmentation Methods: Taxonomy, Trends, Challenges and Future Directions

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3163247

Abstract: Recent advancements in deep learning architectures have extended their application to computer vision tasks, one of which is the segmentation of retinal blood vessels from retinal fundus images. This is a problem that has piqued… read more here.

Keywords: learning retinal; retinal blood; deep learning; segmentation methods ... See more keywords

ScribFormer: Transformer Makes CNN Work Better for Scribble-Based Medical Image Segmentation

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recommendations! Published in 2024 at "IEEE Transactions on Medical Imaging"

DOI: 10.1109/tmi.2024.3363190

Abstract: Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with the local receptive… read more here.

Keywords: branch; segmentation; scribble supervised; supervised segmentation ... See more keywords

Laplacian Coordinates: Theory and Methods for Seeded Image Segmentation

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recommendations! Published in 2021 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2020.2974475

Abstract: Seeded segmentation methods have gained a lot of attention due to their good performance in fragmenting complex images, easy usability and synergism with graph-based representations. These methods usually rely on sophisticated computational tools whose performance… read more here.

Keywords: image; laplacian coordinates; segmentation; image segmentation ... See more keywords

Mpox lesion counting with semantic and instance segmentation methods

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recommendations! Published in 2025 at "Journal of Medical Imaging"

DOI: 10.1117/1.jmi.12.3.034506

Abstract: Abstract. Purpose Mpox is a viral illness with symptoms similar to smallpox. A key clinical metric to monitor disease progression is the number of skin lesions. Manually counting mpox skin lesions is labor-intensive and susceptible… read more here.

Keywords: instance segmentation; segmentation; lesion; lesion counting ... See more keywords

Preliminary process in blast cell morphology identification based on image segmentation methods

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recommendations! Published in 2020 at "International Journal of Electrical and Computer Engineering"

DOI: 10.11591/ijece.v10i6.pp5714-5725

Abstract: The diagnosis of blood disorders in developing countries usually uses the diagnostic procedure Complete Blood Count (CBC). This is due to the limitations of existing health facilities so that examinations use standard microscopes as required… read more here.

Keywords: segmentation methods; process; blast cell; image ... See more keywords

Deep learning-based tooth segmentation methods in medical imaging: A review

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recommendations! Published in 2024 at "Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine"

DOI: 10.1177/09544119231217603

Abstract: Deep learning approaches for tooth segmentation employ convolutional neural networks (CNNs) or Transformers to derive tooth feature maps from extensive training datasets. Tooth segmentation serves as a critical prerequisite for clinical dental analysis and surgical… read more here.

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