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Adnexal Mass Segmentation with Ultrasound Data Synthesis.

C. Lebbos, J. Barcroft, J. Tan, J. Müller, M. Baugh, A. Vlontzos, S. Saso, and B. Kainz. ASMUS@MICCAI, volume 13565 of Lecture Notes in Computer Science, page 106-116. Springer, (2022)

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Matthew Mellon

Matthew David

Matthew Smith

Olumuyiwa Matthew

Peter Matthew

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Image-Conditioned Diffusion Models for Medical Anomaly Detection.M. Baugh, H. Reynaud, S. Marimont, S. Cechnicka, J. Müller, G. Tarroni, and B. Kainz. UNSURE@MICCAI, volume 15167 of Lecture Notes in Computer Science, page 117-127. Springer, (2024)Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis.L. Li, H. Wang, M. Baugh, Q. Ma, W. Zhang, C. Ouyang, D. Rueckert, and B. Kainz. CoRR, (2024)DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection.S. Marimont, M. Baugh, V. Siomos, C. Tzelepis, B. Kainz, and G. Tarroni. CoRR, (2023)MoCoSR: Respiratory Motion Correction and Super-Resolution for 3D Abdominal MRI.W. Zhang, B. Basaran, Q. Meng, M. Baugh, J. Stelter, P. Lung, U. Patel, W. Bai, D. Karampinos, and B. Kainz. MICCAI (10), volume 14229 of Lecture Notes in Computer Science, page 121-131. Springer, (2023)nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods.M. Baugh, J. Tan, A. Vlontzos, J. Müller, and B. Kainz. UNSURE@MICCAI, volume 13563 of Lecture Notes in Computer Science, page 103-112. Springer, (2022)Many Tasks Make Light Work: Learning to Localise Medical Anomalies from Multiple Synthetic Tasks.M. Baugh, J. Tan, J. Müller, M. Dombrowski, J. Batten, and B. Kainz. MICCAI (1), volume 14220 of Lecture Notes in Computer Science, page 162-172. Springer, (2023)URCDM: Ultra-Resolution Image Synthesis in Histopathology.S. Cechnicka, J. Ball, M. Baugh, H. Reynaud, N. Simmonds, A. Smith, C. Horsfield, C. Roufosse, and B. Kainz. MICCAI (4), volume 15004 of Lecture Notes in Computer Science, page 535-545. Springer, (2024)Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models.M. Dombrowski, H. Reynaud, M. Baugh, and B. Kainz. ICCV, page 988-998. IEEE, (2023)DISYRE: Diffusion-Inspired Synthetic Restoration for Unsupervised Anomaly Detection.S. Marimont, M. Baugh, V. Siomos, C. Tzelepis, B. Kainz, and G. Tarroni. ISBI, page 1-5. IEEE, (2024)Confidence-Aware and Self-supervised Image Anomaly Localisation.J. Müller, M. Baugh, J. Tan, M. Dombrowski, and B. Kainz. UNSURE@MICCAI, volume 14291 of Lecture Notes in Computer Science, page 177-187. Springer, (2023)

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Disambiguation of "Baugh, Matthew"

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Adnexal Mass Segmentation with Ultrasound Data Synthesis.

Please choose a person to relate this publication to

Matthew Mellon

Matthew David

Matthew Smith

Olumuyiwa Matthew

Peter Matthew

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Baugh, Matthew"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Adnexal Mass Segmentation with Ultrasound Data Synthesis.

Please choose a person to relate this publication to

Matthew Mellon

Matthew David

Matthew Smith

Olumuyiwa Matthew

Peter Matthew

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Adnexal Mass Segmentation with Ultrasound Data Synthesis.