Training deep learning models generally requires large, costly datasets which can limit their application towards in-house segmentation tasks. This study investigates the trade-off in dataset size within the context of pelvic multi-organ MR segmentation where we evaluate the performance of nnU-Net, a well-known segmentation model, under conditions of limited domain and data availability. 12 participants undergoing treatment on...

Monitoring the morphological traits of farmed fish is pivotal in understanding growth, estimating yield, artificial breeding, and population-based investigations. Currently, morphology measurements mostly happen manually and sometimes in conjunction with individual fish imaging, which is a time-consuming and expensive procedure. In addition, extracting useful information such as fish yield and detecting small variations due to...

Marine scientists use remote underwater image and video recording to survey fish species in their natural habitats. This helps them get a step closer towards understanding and predicting how fish respond to climate change, habitat degradation and fishing pressure. This information is essential for developing sustainable fisheries for human consumption, and for preserving the environment. However, the enormous volume of collect...