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.

Bibliografische gegevens
Hoofdauteurs: Riju, Tanjim Islam, Ramisha, Tahsin Tanim, Aksa, Nusrat Billah, Kabir, Johan H
Andere auteurs: Alam, Md. Golam Rabiul
Formaat: Thesis
Taal:English
Gepubliceerd in: Brac University 2024
Onderwerpen:
CNN
State space models
MedMamba
MedMambaSE
Maternal-fetal
Artificial intelligence > Medical applications.
Fetuses-Ultrasonic imaging.
Diagnostic imaging > Digital techniques.
Online toegang:http://hdl.handle.net/10361/24337

Internet

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

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