Look-up in Google Scholar
Full metadata record
Mora Colque, Rensso
Estacio Cerquin, Laura Jovani
2023-02-08T16:06:37Z
2023-02-08T16:06:37Z
2023-02-08T16:06:37Z
2023-02-08T16:06:37Z
2022
1076272
https://hdl.handle.net/20.500.12590/17432
We present a method based on a generative model for detection of anomalies such as prosthesis, implants, screws, zippers, and metals in Two-dimensional (2D) radiographs. The generative model is trained following an unsupervised fashion using clinical radiographs as well as simulated data, neither of them containing anomalies. Our approach employs a reconstruction loss and a latent space consistency loss which have the benefit of identifying similarities which are forced to reconstruct X-rays without anomalies. In order to detect images with anomalies, an anomaly score is also computed employing the reconstruction loss and the latent space consistency loss. Additionally, the Frechet distance is introduced as part of the reconstruction loss. These losses are computed between an input X-ray and the one reconstructed by the proposed generative model. Validation was performed using clinical pelvis radiographs. We achieved an Area Under the Curve (AUC) of 0.77 and 0.83 with clinical and synthetic data, respectively. The results demonstrated a good accuracy of the proposed method for detecting outliers as well as the advantage of utilizing synthetic data for the training stage. (es_PE)
Tesis (es_PE)
application/pdf (es_PE)
eng (es_PE)
Universidad Católica San Pablo (es_PE)
SUNEDU
info:eu-repo/semantics/openAccess (es_PE)
https://creativecommons.org/licenses/by/4.0/ (es_PE)
Universidad Católica San Pablo (es_PE)
Repositorio Institucional - UCSP (es_PE)
reponame:UCSP-Institucional
instname:Universidad Católica San Pablo
instacron:UCSP
Anomaly Detection (es_PE)
Unsupervised Learning (es_PE)
Generative Adversarial Networks (es_PE)
Pelvic radiographs (es_PE)
Unsupervised anomaly detection in 2D radiographs using generative models (es_PE)
info:eu-repo/semantics/masterThesis (es_PE)
Universidad Católica San Pablo. Departamento de Ciencia de la Computación (es_PE)
Ciencia de la Computación (es_PE)
Maestría (es_PE)
Maestra en Ciencia de la Computación (es_PE)
PE (es_PE)
http://purl.org/pe-repo/ocde/ford#1.02.01 (es_PE)
https://purl.org/pe-repo/renati/level#maestro (es_PE)
42846291
https://orcid.org/0000-0003-4734-8752 (es_PE)
46913887
611017 (es_PE)
Ochoa Luna, José Eduardo (es_PE)
Cámara Chávez, Guillermo (es_PE)
Menotti, David (es_PE)
Montoya Zegarra, Javier (es_PE)
https://purl.org/pe-repo/renati/type#tesis (es_PE)
Privada asociativa
info:eu-repo/semantics/publishedVersion (es_PE)



This item is licensed under a Creative Commons License Creative Commons