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.

Détails bibliographiques
Auteurs principaux: Riju, Tanjim Islam, Ramisha, Tahsin Tanim, Aksa, Nusrat Billah, Kabir, Johan H
Autres auteurs: Alam, Md. Golam Rabiul
Format: Thèse
Langue:English
Publié: Brac University 2024
Sujets:
CNN
State space models
MedMamba
MedMambaSE
Maternal-fetal
Artificial intelligence > Medical applications.
Fetuses-Ultrasonic imaging.
Diagnostic imaging > Digital techniques.
Accès en ligne:http://hdl.handle.net/10361/24337

Internet

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

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