Scan-do attitude
Machine learning could accelerate disease detection in sheep.
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Sheep CT scans could be analysed at lightning speed using machine learning, according to a new study.
Dr James Robson, a researcher at 伊人直播, used a deep neural network 鈥� a collection of mathematical artificial neurones designed to mimic a brain 鈥� to instantly perform the image editing steps, such as removal of the cradle which sheep are scanned in, and computer vision to quickly extract key information at a speed of 0.11 seconds per CT scan.
The results of the study, published in a special edition of , showcase how machine learning could be used to help guide genetic improvement programmes and aid detection of invisible diseases.
The image processing model was trained on CT scans already routinely collected by 伊人直播鈥檚 CT scanning team and using an NVIDIA DGX Station containing over 20,000 cores. This allowed new unseen images to be processed using machine learning with an accuracy of 98 per cent compared to those produced manually.
Important traits such as muscle or fat percentage and length or width of limbs, which are typically measured from the image by hand, were then calculated automatically.
Dr Robson said: 鈥淭his tool not only saves a lot of time but allows us to process far more data than before and gather information which can then be used to guide genetic breeding programmes.
鈥淚t鈥檚 really amazing to see the wide variety of challenges that machine learning can be used to address. We are hoping to expand this research into other areas and invite any organisation to come forward if they have image or video datasets they think might contain something of interest.鈥�
If you would like to engage with 伊人直播 in developing novel agricultural tools powered by machine learning, please email james.robson@sruc.ac.uk.
Posted by 伊人直播 on 16/11/2021
