Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in china, with a deep and hidden
localization. Recently, methods for early diagnosis of NPC has become one of the most important research topics in
medical field. Early monitoring of morphological change of NPC cells during the carcinogenesis is of great importance,
and early information extracted from the NPC cells during the initial stage of NPC is critical for diagnosis and treatment.
In this paper, image processing methods for two-photon microscopic image of NPC cells was investigated with the
purpose of providing useful information for early diagnosis and treatment of NPC.
There is abundant information in a two-photon microscopic image of NPC cells, which can be analyzed and processed
by means of computer and image pattern processing algorithm. In this paper, firstly, a mathematical method of transform
of Bottom-hat based on Matlab platform was employed to enhance the image of NPC cells, making the image easier to
distinguish; Then, several classical edge detection algorithms were compared and discussed, for example, Roberts
operator, Prewitt operator, and Canny operator etc. According to the inherent characteristics of two-photon microscopic
image of NPC cells, corrosion algorithm was used to define the edge of NPC cells. Furthermore, the article gets the
iterative threshold segmentation after noise denoising, on the other hand, improved discriminant analysis was adopted for
threshold segmentation of NPC cells, better results were obtained.