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Unsupervised segmen...
Unsupervised segmentation and data augmentation in image sequences of skeletal muscle contraction by cycle-consistent generative adversarial network
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- Saboori, Arash (författare)
- Umeå universitet,Institutionen för strålningsvetenskaper
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- Grönlund, Christer (författare)
- Umeå universitet,Institutionen för strålningsvetenskaper
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(creator_code:org_t)
- IEEE, 2023
- 2023
- Engelska.
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Ingår i: 2023 international conference on modeling, simulation & intelligent computing (MoSICom). - : IEEE. - 9798350393415 - 9798350393422 ; , s. 474-479
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This paper investigates a method addressing the unsupervised segmentation and joint data augmentation in medical ultrasound imaging based on the modified CycleGAN. Accurate quantification of fascia and muscle is the key for the diagnostics of neuromuscular disorders based on the analysis of image sequences of skeletal muscle contraction. Although the Deep Learning (DL) models represent encouraging results, some challenges exist. The traditional models don't consider the complex interaction between tissues within a muscle and its surroundings, which reduces the performance of the fascia segmentation. Also, the DL requires many annotated datasets, which ignores dealing with noisy and complex ultrasound images. To overcome these issues, we propose a method to generate realistic images, and then present an unsupervised fascia segmentation method. The results show that our method improves the segmentation accuracy in noisy and complex ultrasound images compared to the traditional methods.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Nyckelord
- CycleGAN
- fascia
- segmentation
- skeletal muscle contraction
- ultrasound imaging
- unsupervised segmentation
- Complex networks
- Deep learning
- Diagnosis
- Generative adversarial networks
- Image enhancement
- Image segmentation
- Medical imaging
- Ultrasonic imaging
- Data augmentation
- Image sequence
- Ultrasound images
- Unsupervised data
- Muscle
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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