Research Projects

Improving karyotyping of human chromosomes using deep learning

Karyotyping based on biomedical image processing acts an crucial role in gene analysis, enabling geneticist to diagnose several genetic diseases and genetic disorder such as Down syndrome, leukemia, etc. In current workflow, geneticist use conventional biomedical image processing method to separate the chromosomes either manually or semi-automatically. Karyotyping often requires geneticist to analysis dozens of metaphase images and reorganize the chromosome into 23 pairs and thus is very time consuming. In this research, we building a tool which applies AI to automatically classify the chromosomes, aiding geneticist to detect abnormality in the karyogram of the patients.

Metaphase image of a leukemia patient, captured using microscope

Karyogram of the leukemia patient performed by cytogenetist

Publications:

Nguyen Hong Thinh, Nguyen Huu Hoang Son, Pham Thi Viet Huong, Nguyen Thi Cuc Nhung, Nguyen Thanh Binh Minh, Luu Manh Ha et al., “A Web-based Tool for Semi-interactively Karyotyping the Chromosome Images for Analyzing Chromosome Abnormalities,” 2020 7th NAFOSTED Conference on Information and Computer Science (NICS), Ho Chi Minh City, Vietnam, 2020, pp. 433-437, doi: 10.1109/NICS51282.2020.9335893.

Other information
PI: Dr. Luu Manh Ha, AVITECH

SAME CATEGORY

EEG signal processing from the computer vision perspective

In this work, we study the processing of EEG signals in the image domain, i.e., visualizing the signal in the binary image and applying computer vision techniques for signal smoothing and classification. Some research questions are being investigated: 1. How well can we smooth the signal in the image domain? Here, we plot the interested […]

Vision-based crack detection with crack propagation modeling

In this work, the propagation of cracks on some materials, such as concrete, is analyzed, the best-fit model of which is employed for vision-based crack detection. Some research questions are being investigated: 1. What is the correlation between simulated crack propagation and real-world crack? Here, we measure the fitting errors between best-fit regression models of […]

Machine learning based beacon placement optimization for indoor robots localization

Indoor localization systems usually consist of transceiver with fixed positions, which are called beacons. These beacons act as landmarks for localizing objects that need to be positioned. One can easily see that the positions of beacons have a great impact on the performance of the localization system. The problem of beacon placement optimization is to […]