Classification of Human Blastocyst Quality Using Wavelets and Transfer Learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Embryo culture and transfer are the procedure of maturation and transmission of the embryo into the uterus. This procedure is one of a stage in the series of in vitro fertilization processes, better known as IVF. The selection of good quality embryos to be implanted presents a problem because of the blastocyst image. Blastocyst image is a very intricate texture to be visually determined, which is good or poor quality. This research aims to implement the pre-trained Inception-v3 network to predict blastocyst quality with add image pre-processing using wavelets. Using only 249 of human blastocyst microscope images, we developed an accurate classifier that can classify blastocyst quality with a transfer learning. The experiment with twenty epochs, the accuracy of training for only raw blastocyst images is 95%, and the best training accuracy uses a pre-processing image with Daubechies 6-tap of 99.29%. Our model was then tested on the 14 of blastocyst images and classified the images of two kinds of grade with the best accuracy of around 64.29%.

Original languageEnglish
Title of host publicationAdvances in Computer, Communication and Computational Sciences - Proceedings of IC4S 2019
EditorsSanjiv K. Bhatia, Shailesh Tiwari, Su Ruidan, Munesh Chandra Trivedi, K. K. Mishra
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9789811544088
Publication statusPublished - 2021
EventInternational Conference on Computer, Communication and Computational Sciences, IC4S 2019 - Bangkok, Thailand
Duration: 11 Oct 201912 Oct 2019

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


ConferenceInternational Conference on Computer, Communication and Computational Sciences, IC4S 2019


  • Human blastocyst
  • Quality classification
  • Transfer learning
  • Wavelets


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