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.

Библиографические подробности
Главные авторы:	Riju, Tanjim Islam, Ramisha, Tahsin Tanim, Aksa, Nusrat Billah, Kabir, Johan H
Другие авторы:	Alam, Md. Golam Rabiul
Формат:	Диссертация
Язык:	English
Опубликовано:	Brac University 2024
Предметы:	CNN State space models MedMamba MedMambaSE Maternal-fetal Artificial intelligence > Medical applications. Fetuses-Ultrasonic imaging. Diagnostic imaging > Digital techniques.
Online-ссылка:	http://hdl.handle.net/10361/24337

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