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Medical machine learning on the Conversation

We just had a piece on medical machine learning published in the Conversation.

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ACVT technology gets FDA approval

The ACVT has been working with LBT Innovations, a South Australian medical device company, for more than 5 years on a new form of medical device to automate the reading of Agar plates.  The processing of Agar plates is an important and time-consuming part of the normal operation of hospitals and clinics around the world. […]

Posted in Medical Imaging, News, Research, Technology Transfer | Tagged , , , , |

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Number 2 in ImageNet Scene Parsing Challenge 2016

We’ve had another great year in the ImageNet competition.  We came 2nd in the Scene Parsing challenge, which requires pixelwise segmentation of a large set of images into 150 classes of things and stuff.  The ImageNet Challenge is one of the most hotly contested challenges in Computer Vision, and is constantly updated to reflect the current […]

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ACVT Medical Imaging tech achieves 98% in FDA trials

From the LBT annual report: A ten-week pivotal clinical trial at TriCore Reference Laboratories in New Mexico during July and August 2015 tested APAS against a panel of microbiologists. Culture plates from 5,500 patients were processed by APAS and simultaneously assessed by a panel of independent qualified microbiologists. The results showed that APAS achieved over […]

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World’s best Coco

The Microsoft COCO Captioning Challenge is designed to spur the development of algorithms producing image captions that are informative and accurate. There are 18 teams all together and our attributes based image captioning framework currently achieves the best result on 3 evaluation metrics (BLEU-1,2,3) out of 7. We also achieve the top-5 ranking on the […]

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ACVT semantic image segmentation technique tops in the PASCAL VOC Challenge

Researchers at ACVT have developed new “Deep Structured Learning” techniques that set up the new state-of-the-art semantic image segmentation record in the PASCAL VOC Challenge, which is organised by Oxford University. Semantic image segmentation is one of the tasks and probably the most challenging one, which is to label each pixel in images. Deep Learning is the […]

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LBT Innovations presents APAS study results

LBT Innovations (ASX:LBT) has published the details of its extensive study into the accuracy of its Automated Plate Assessment System (APAS). Results from the study were released in a poster presentation at the Australian Society for Microbiology annual meeting in Melbourne this week. The poster confirms the headline result that, comparing the screening of hundreds of clinical samples by APAS […]

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CRC Success

It has just been announced that the Data to Decisions (D2D) CRC application was successful.   The ACVT forms a major node of the D2D CRC, being responsible for the analytics program within the CRC.  The aim of the D2D CRC  is to develop robust data analysis tools applicable to problems of importance to Defence, and […]

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ARC Centre of Excellence for Robotic Vision (CE140100016)

ACVT researchers Prof. Ian Reid, Prof. Anton van den Hengel, Associate Prof. Chunhua Shen and Dr. Gustavo Carneiro are part of a team that has been awarded a prestigious ARC Centre of Excellence in Robotic Vision. The Centre has received $19M of funding and will conduct a 7-year program of research with the following focus […]

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Automated analysis of multi-modal medical data using deep belief networks (DP140102794)

Dr Gustavo  Carniero has won a 3 year ARC Discovery Grant valued at $295,000. The project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a […]

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The Australian Centre for Visual Technologies
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Level 5, Ingkarni Wardli,
The University of Adelaide,
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