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ISSN:
1386-5056
eISSN:
1872-8243
Disciplines
(Field of Science):
- information and communication technology (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- medical biology (Medical and Health Sciences )
- medical sciences (Medical and Health Sciences )
- health sciences (Medical and Health Sciences )
- family studies (Family studies)
- biotechnology (Natural sciences)
- computer and information sciences (Natural sciences)
(Field of Science)
Ministry points: Help
| Year | Points | List |
|---|---|---|
| Year 2025 | 140 | Ministry scored journals list 2024 |
| Year | Points | List |
|---|---|---|
| 2025 | 140 | Ministry scored journals list 2024 |
| 2024 | 140 | Ministry scored journals list 2024 |
| 2023 | 140 | Ministry Scored Journals List |
| 2022 | 140 | Ministry Scored Journals List 2019-2022 |
| 2021 | 140 | Ministry Scored Journals List 2019-2022 |
| 2020 | 140 | Ministry Scored Journals List 2019-2022 |
| 2019 | 140 | Ministry Scored Journals List 2019-2022 |
| 2018 | 40 | A |
| 2017 | 40 | A |
| 2016 | 30 | A |
| 2015 | 30 | A |
| 2014 | 40 | A |
| 2013 | 35 | A |
| 2012 | 30 | A |
| 2011 | 30 | A |
| 2010 | 32 | A |
Model:
Hybrid
Points CiteScore:
| Year | Points |
|---|---|
| Year 2023 | 8.9 |
| Year | Points |
|---|---|
| 2023 | 8.9 |
| 2022 | 9.5 |
| 2021 | 8 |
| 2020 | 7.1 |
| 2019 | 5.8 |
| 2018 | 5.3 |
| 2017 | 5.4 |
| 2016 | 6.2 |
| 2015 | 5.9 |
| 2014 | 5.3 |
| 2013 | 5.6 |
| 2012 | 6 |
| 2011 | 5.7 |
Impact Factor:
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Sherpa Romeo:
Papers published in journal
Filters
total: 1
Catalog Journals
Year 2024
-
Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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