Óbuda University - CUDA Teaching Center

Current projects

Cell nuclei detection using multiple GPGPUs
Sándor Szénási, Miklós Kozlovszky, Zoltán Vámossy
Several segmentation procedures are based on the segmentation of the image and a lot of them need the number and the locations of the cells. The aim of our research is developing a new data parallel algorithm that can be implemented even in a GPGPU environment and that is capable of counting hematoxylin eosin (HE) stained cell nuclei and of identifying their exact locations and sizes (using a variation of the region growing method). The new method has three levels of parallelization:
  o Parallelization of the region growing method to use 1 thread for processing of each contour points.
  o Starting more region growings in the GPGPU at the same time to fully utilize the processing power.
  o Using multiple GPGPUs based on the split-and-merge method.

Detection of epithelial cells using GPGPU
Sándor Szénási
Epithelial tissues line the cavities and surfaces of structures throughout the body. They also form many glands. In HE stained colon tissue samples, epithelial cells appear around the glands and at the edge of the whole sample (surface epithelium). After the cell nuclei detection, we have to determine that an appropriate nucleus belongs to an epithelial cell or not. The method developed by us is based on the idea that that the epithelial cells have some particular attributes compared to the other cells:
  o Density of the epithelial cell nuclei groups differs from the average density of the other cells of the tissue sample:
     • High density in one direction.
     • Relatively small density orthogonally.
     • Average density in the other orthogonal direction.
  o Epithelial cells usually form a chain.
Security issues of GPGPU programming
Szabolcs Sergyán, Sándor Szénási, Zoltán Vámossy
Nowadays GPGPU programming becomes more and more general, especially in the field of High Performance Computing. In the first time, in case of games and initial research projects, data security was not an important factor. However nowadays, there are several GPGPU applications working with sensitive (personal, business, governmental) data. This project raises several questions about the possible security holes and attack methods:
  o Hardware and software deficiencies
  o Non-deterministic behaviour
  o Memory leaking
  o Malware attacks