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.

Dettagli Bibliografici
Autori principali: Riju, Tanjim Islam, Ramisha, Tahsin Tanim, Aksa, Nusrat Billah, Kabir, Johan H
Altri autori: Alam, Md. Golam Rabiul
Natura: Tesi
Lingua:English
Pubblicazione: Brac University 2024
Soggetti:
CNN
State space models
MedMamba
MedMambaSE
Maternal-fetal
Artificial intelligence > Medical applications.
Fetuses-Ultrasonic imaging.
Diagnostic imaging > Digital techniques.
Accesso online:http://hdl.handle.net/10361/24337

Accesso online

http://hdl.handle.net/10361/24337

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