Hyperspectral Image Cell Segmentation and Tracking

The project deals with segmentation and classification of florescent samples of lunge cells captured in a hyperspectral microscope (FRET). The output of such a measurement could serve the search for thorough understanding of intercellular biological process and malignant diseases.

Analyzing the samples that were supplied is a challenging task, mainly because the cells in the samples were very dense and sometimes overlapped.

Segmentation and tracking of the cells was accomplished, almost fully automated (only in the first time lapse user supervision is needed). The method we use combines techniques from various fields in computer vision in order to achieve a robust and versatile segmentation tool.

Hyperspectral Image Cell Segmentation & Tracking

 

poster-3-2-15-2400

Collaboration:

Arie Nakhmani, Ph.D.