Detail publikace

Attention-based Multiscale Deep Neural Network for Diagnosis of Polycystic Ovary Syndrome Using Ovarian Ultrasound Images

RASHID, S. KARNATI, M. AGGARWAL, G. DUTTA, M. SIKORA, P. BURGET, R.

Originální název

Attention-based Multiscale Deep Neural Network for Diagnosis of Polycystic Ovary Syndrome Using Ovarian Ultrasound Images

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Polycystic Ovary Syndrome (PCOS) is a hormonal disorder that impacts a significant proportion of women in their reproductive years. It results in irregular menstrual cycles and elevated levels of androgens, known as male hormones. Women with PCOS often have ovaries that develop numerous small fluid-filled sacs called follicles, but they fail to release eggs regularly. While the precise cause of PCOS remains unknown, early identification and weight loss can help mitigate the risk of long-term complications. In this study, a novel attention-based multiscale convolutional neural network (AMCNN) is proposed for the detection of PCOS. The utilization of dilated convolution aids in preserving the multi-scale features with fewer parameters. The integration of multiscale characteristics is achieved by the attention mechanism, which enhances the importance of features within significant channels. The experimental results demonstrate the superior performance of the AMCNN, surpassing other prominent algorithms with an accuracy of 98.79%, proving its effectiveness for medical industrial applications.

Klíčová slova

polycystic ovary syndrome, deep learning, convolutional neural networks, ultrasound images, diagnosis

Autoři

RASHID, S.; KARNATI, M.; AGGARWAL, G.; DUTTA, M.; SIKORA, P.; BURGET, R.

Vydáno

5. 12. 2023

Nakladatel

IEEE Computer Society

Místo

Ghent

ISBN

979-8-3503-9328-6

Kniha

2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

ISSN

2157-023X

Periodikum

International Congress on Ultra Modern Telecommunications and Control Systems and Workshops

Stát

neuvedeno

Strany od

44

Strany do

49

Strany počet

6

URL

https://ieeexplore.ieee.org/document/10333275

BibTex

@inproceedings{BUT185578,
  author="Suzain {Rashid} and Mohan {Karnati} and Garmia {Aggarwal} and Malay Kishore {Dutta} and Pavel {Sikora} and Radim {Burget}",
  title="Attention-based Multiscale Deep Neural Network for Diagnosis of Polycystic Ovary Syndrome Using Ovarian Ultrasound Images",
  booktitle="2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)",
  year="2023",
  journal="International Congress on Ultra Modern Telecommunications and Control Systems and Workshops",
  pages="44--49",
  publisher="IEEE Computer Society",
  address="Ghent",
  doi="10.1109/ICUMT61075.2023.10333275",
  isbn="979-8-3503-9328-6",
  issn="2157-023X",
  url="https://ieeexplore.ieee.org/document/10333275"
}