Registration of in vivo fluorescence endomicroscopy images based on feature detection.
The confocal fluorescence endomicroscopy is an emerging technology for imaging the living subjects inside the animals and human bodies. However, the acquired images vary, due to two degrees of freedom-tissue movement and tissue expansion/contraction. This makes the 3D reconstruction of them difficult and thus limits the clinic applications. In this chapter, we propose a feature-based registration algorithm to correct the distortions between these fluorescence images. The good alignment enables us to reconstruct and visualize the 3D structure of the living cells and tissues in real time, which provides the opportunity for the clinicians to diagnose various diseases, including the early-stage cancers. Experimental results on a collection of more than 300 confocal fluorescence images of the gerbil brain microvasculature clearly demonstrate the effectiveness and accuracy of our method.
Zhao
Feng
F
School of Computer Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
Cheong
Lee Sing
LS
Lin
Feng
F
Qian
Kemao
K
Seah
Hock Soon
HS
Kung
Sun-Yuan
SY
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000098:blood supply; D019295:Computational Biology; D003199:Computer Systems / Q000706:statistics & numerical data; D005849:Gerbillinae; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D021621:Imaging, Three-Dimensional / Q000706:statistics & numerical data; D051379:Mice; D008833:Microcirculation; D018613:Microscopy, Confocal / Q000706:statistics & numerical data*; D008856:Microscopy, Fluorescence / Q000706:statistics & numerical data*; D010865:Pilot Projects