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Deep Reinforcement Learning for the Active Extraction and Visualisation of Optimal Biomarkers in Medical Images

This bioengineering project will develop novel methods for discovering and visualising optimal biomarkers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance the state of the art in medical image analysis given that it will allow an efficient analysis of large dimensionality inputs in their original high resolution. In addition, our project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes.

  • October 2019 - Two Ultrasound in Medicine & Biology papers published, and Gabriel has been interviewed by The Advertiser about his work!  
  • October 2019 - Gustavo and Gabriel are part of a group selected as a finalist for the Minister's Research and Innovation Award with the project Computer Aided Diagnosis using Artificial Intelligence in Colorectal Polyps, as part of the 2019 SA Health Awards.
  • September 2019 Gabriel Maicas et al. have a paper accepted to MedIA
  • June 2019 Prof. Nascimento and Prof. Carneiro have a paper accepted to PAMI
  • May 2019 - Prof. Carneiro has a paper accepted to ICML'19
  • February 2019 - Prof. Carneiro has a paper accepted to CVPR'19
  • February 2019: Welcome Research Assistant Dr. Gabriel Maicas
  • February - June 2019: Prof. Gustavo Carneiro spend SSP leave at IST (Portugal) and TUM (Germany), as a Humboldt Fellow
  • December 2018: Welcome PhD student Hossein Askari
  • December 2018: Congrats Gabriel Maicas for PhD and Dean’s Commendation for Doctoral Thesis Excellence!
  • October 2018: Workshop DLMIA @ MICCAI 2018
  • October 2018: Workshop BIA @ MICCAI 2018
  • October 2018: Oral presentation by Gabriel Maicas @ MICCAI 2018
  • October 2018: Welcome PhD student Renato Hermoza Aragones
  • October 2018: Prof. Carneiro visited IST-Lisbon and TUM on an Epic grant

Publications

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Pre and Post-hoc Diagnosis and Interpretation of
Malignancy from Breast DCE-MRI

paper
video

Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro. In Medical Image Analysis (MedIA) 2019.

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Deep Learning based femoral cartilage automatic segmentation in ultrasound imaging for robotic knee arthroscopy

M. Antico, F. Sasazawa, M. Dunnhofer, S.M. Camps, A.T. Jaiprakash, A.K. Pandey, R. Crawford, G. Carneiro, D. Fontanarosa. Ultrasound in Medicine & Biology (UMB). 2019. 

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Automatic quality assessment of transperineal ultrasound images of the male pelvic region using deep learning. 

S.M. Camps, T. Houben, G. Carneiro, C. Edwards, M. Antico, M. Dunnhofer, E.G.H.J. Martens, J.A. Baeza, B.G.L. Vanneste, E.J. van Limbergen, P.H.N. de With, F. Verhaegen, D. Fontanarosa. Ultrasound in Medicine & Biology (UMB). 2019.

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One shot segmentation: unifying rigid detection and non-rigid segmentation using elastic regularization

paper

Jacinto Nascimento, Gustavo Carneiro.  In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019.

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Bayesian Generative Active Deep Learning

paper

Toan Tran, Thanh-Toan Do, Ian Reid, Gustavo Carneiro. International Conference on Machine Learning (ICML) 2019.

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A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning

paper

Thanh-Toan Do, Toan Tran, Ian Reid, Vijay Kumar, Tuan Hoang, Gustavo Carneiro. Conference on Computer Vision and Pattern Recognition (CVPR) 2019.

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One-stage Five-class Polyp Detection and Classification

paper

Yu Tian, Leonardo Z.C.T. Pu, Rajvinder Singh, Alastair D. Burt, Gustavo Carneiro. International Symposium on Biomedical Imaging (ISBI) 2019.

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Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI

paper

Gabriel Maicas, Gerard Snaauw, Andrew Bradley, Ian Reid, Gustavo Carneiro. International Symposium on Biomedical Imaging (ISBI) 2019.

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End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging

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Gerard Snaauw, Dong Gong, Gabriel Maicas, Anton Van Den Hengel, Wiro Niessen, Johan Verjans, Gustavo Carneiro. International Symposium on Biomedical Imaging (ISBI) 2019.

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Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks

paper

Zhibin Liao, Tom Drummond, Ian Reid, Gustavo Carneiro. In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2018.

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Multi-modal Cycle-consistent Generalized Zero-Shot Learning

paper

Rafael Felix, Vijay Kumar B G, Ian Reid, Gustavo Carneiro. European Conference on Computer Vision (ECCV) 2018.

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Bayesian Instance Segmentation in Open Set World

paper

Trung Pham, Vijay Kumar B G, Thanh-Toan Do, Gustavo Carneiro, Ian Reid. European Conference on Computer Vision (ECCV) 2018.

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One-class Gaussian process regressor for quality assessment of transperineal ultrasound images

paper

Saskia M. Camps, Tim Houben, Davide Fontanarosa, Christopher Edwards, Maria Antico, Matteo Dunnhofer, Esther G.H.J. Martens, Jose A. Baeza, Ben G.L. Vanneste, Evert J. van Limbergen, Peter H.N. de With, Frank Verhaegen, Gustavo Carneiro. International conference on Medical Imaging with Deep Learning (MIDL) 2018.

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Training Medical Image Analysis Systems like Radiologists

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video

Gabriel Maicas, Andrew Bradley, Jacinto Nascimento, Ian Reid, Gustavo Carneiro. International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI) 2018. 

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Prof. Gustavo Carneiro

Lead Chief Investigator

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Prof. Andrew Bradley

Chief Investigator

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Prof. Lyle Palmer

Chief Investigator

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Assist. Prof. Jacinto Nascimento

Associate Investigator

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Dr. Gabriel Maicas

Research Assistant

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Mr. 
Hossein Askari Lyarjdameh

Ph.D. Student

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Dr. 

Ph.D. Student

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TBD

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Our Contacts

Address and email

ADDRESS
North Terrace
Ingkarni Wardli Building, Room 5.42
University of Adelaide
Adelaide, SA 5005, Australia

CONTACT
Email: gustavo.carneiro@adelaide.edu.au