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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.

  • March 2020 - Gabriel Maicas is interviewed by The Lead
  • March 2020 - 1 IEEE Acess and 1 GIE paper accepted
  • February 2020 - Prof. Carneiro has a paper accepted to MedIA
  • January 2020 - 3 papers accepted to ISBI 2020
  • December 2019 - Prof. Carneiro has a paper accepted to MedIA
  • November 2019 - Prof. Carneiro was awarded an ARC Future Fellowship!
  • November 2019 -  PhD student Renato Hermoza Aragones passed major review - Congrats Renato!
  • 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

Mobirise

Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT

paper

Saskia Glaser, Gabriel Maicas, Sergei Bedrikovetski, Tarik Sammour, Gustavo Carneiro. In International Symposium on Biomedical Imaging (ISBI) 2020.

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Photoshopping Colonoscopy Video Frames

paper

Yuyuan Liu, Yu Tian, Gabriel Maicas, Leonardo ZCT Pu, Rajvinder Singh, Johan W Verjans, Gustavo Carneiro. In International Symposium on Biomedical Imaging (ISBI) 2020.

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Unsupervised Task Design to Meta-Train Medical Image Classifiers

paper

Gabriel Maicas, Cuong Nguyen, Farbod Motlagh, Jacinto C Nascimento, Gustavo Carneiro. In International Symposium on Biomedical Imaging (ISBI) 2020.

Mobirise

Deep Learning Uncertainty and Confidence Calibration for the Five-class Polyp Classification from Colonoscopy

paper

Gustavo Carneiro, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh, Alastair Burt.  In Medical Image Analysis (MedIA) 2020.

Mobirise

Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning

paper

Yaqub Jonmohamadi , Yu Takeda, Fengbei Liu , Fumio Sasazawa, Gabriel Maicas, Ross Crawford, Jonathan Roberts, Ajay Pandey, Gustavo Carneiro. IEEE Access 2020.

Mobirise

Computer-aided diagnosis for characterization of colorectal lesions: a comprehensive software including serrated lesions.

PubMed

Leonardo Zorron Cheng Tao Pu, Gabriel Maicas, Yu Tian, Takeshi Yamamura, Masanao Nakamura, Hiroto Suzuki, Gurfarmaan Singh, Khizar Rana, Yoshiki Hirooka, Alastair D. Burt, Mitsuhiro Fujishiro, Gustavo Carneiro, Rajvinder Singh. Gastrointestinal Endoscopy (GIE) 2020.

Mobirise

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.

Mobirise

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

paper

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). 2020. 

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

paper

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). 2020.

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Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images

paper

Matteo Dunnhofer, Maria Antico, Fumio Sasazawa, Yu Takeda, Saskia Camps, Niki Martinel, Christian Micheloni, Gustavo Carneiro, Davide Fontanarosa. In Medical Image Analysis (MedIA) 2019.

Mobirise

Producing radiologist quality reports for interpretable deep learning

paper

William Gale, Gustavo Carneiro, Luke Oakden-Rayner, Lyle Palmer, Andrew Bradley. International Symposium on Biomedical Imaging (ISBI) 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.

Mobirise

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.

Mobirise

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.

Mobirise

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

paper

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

Mobirise

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.

Mobirise

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.

Mobirise

Training Medical Image Analysis Systems like Radiologists

paper
video

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

Invited Talks

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O(N) Training of Triplet Nets for Distance Metric Learning

Talk at Technical University of Munich, and Ulm University, 2019

Prof. Gustavo Carneiro

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

Talk at Technical University of Munich, Instituto Superior Tecnico and Helmhotz research centre, 2018 and 2019

Prof. Gustavo Carneiro

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Dr. Luke Oakden Rayner

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Machine learning capability at AIML with examples of projects that identify organs from MRI and ultra-sound

Talk at Robinson Research Institute at the Workshop: Machine Learning to identify endometriosis before surgery, 2020

Dr. Gabriel Maicas

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Machine Learning (ML) for Medical Image Computing (MIC) and Computer Assisted Intervention (CAI)

5th ADVANCED IMAGING MASTERCLASS (AIM): ENDOSCOPIC PATHWAYS...
DIAGNOSIS, THERAPY, THE FUTURE, 2020

Prof. Gustavo Carneiro

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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

TBD

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TBD

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