Earth, Atmosphere & Environment Sciences
Title : | Pilot study on demonstrating Deep learning based non- invasive Ultrasound tool for assessing sexual maturation of Asian sea bass Lates calcarifer |
Area of research : | Earth, Atmosphere & Environment Sciences |
Focus area : | Ocean science |
Principal Investigator : | Dr. Senthil Murugan, ICAR, CIBA |
Timeline Start Year : | 2024 |
Timeline End Year : | 2025 |
Details
Executive Summary : | The project aims to develop a non-invasive ultrasound technique for detecting the sex, assessing
the gonadal maturity stages of both male and female fishes of brackishwater aquaculture
importance. The findings will help in obtaining stress free spawning without any obstruction in
the reproductive success of captive brooders. The technique to be developed will be of great
help for private entrepreneurs to make use of user-friendly technique which will unblock the
hurdles to have a strengthened scientific knowledge and facilities to start up the fin fish
hatchery especially the foremost frontier of brooders development and breeding. The stress-
free spawning is achieved through deep learning techniques. The ultrasound images are
acquired and preprocessed using windowing, segmentation and feature extraction to remove
the speckle noise which extracts texture features, shape features, histogram, correlogram
features and morphology features. The processed image is fed to the deep learning technique
to identify the gonads stages which are classified into immature, mature, ripe and running.
Transfer learning is used to populate more images for training the system to provide better
accuracy. The Generative Adversarial Network (GAN) is used to classify the gonad stages. Finally,
the stress-free deep learning results are compared with the histology data for validating the test
results |
Co-PI: | Dr. Aritra Bera, Scientist, CIBA |
Total Budget (INR): | 29,96,156 |
Organizations involved