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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Riju, Tanjim Islam, Ramisha, Tahsin Tanim, Aksa, Nusrat Billah, Kabir, Johan H
Άλλοι συγγραφείς: Alam, Md. Golam Rabiul
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2024
Θέματα:
CNN
State space models
MedMamba
MedMambaSE
Maternal-fetal
Artificial intelligence > Medical applications.
Fetuses-Ultrasonic imaging.
Diagnostic imaging > Digital techniques.
Διαθέσιμο Online:http://hdl.handle.net/10361/24337

Διαδίκτυο

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

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