Fetal plane classification from 2D-ultrasound images leveraging squeeze and excitation self-attention mechanism for feature recalibration in MedMamba

Fetal plane classification from 2D-ultrasound images leveraging squeeze and excitation self-attention mechanism for feature recalibration in MedMamba

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

書誌詳細
主要な著者:	Riju, Tanjim Islam, Ramisha, Tahsin Tanim, Aksa, Nusrat Billah, Kabir, Johan H
その他の著者:	Alam, Md. Golam Rabiul
フォーマット:	学位論文
言語:	English
出版事項:	Brac University 2024
主題:	CNN State space models MedMamba MedMambaSE Maternal-fetal Artificial intelligence > Medical applications. Fetuses-Ultrasonic imaging. Diagnostic imaging > Digital techniques.
オンライン･アクセス:	http://hdl.handle.net/10361/24337

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