**4. Diabetic retinopathy study through retinal image fusion**

Hypoxia of the retina is believed to be a factor in the development of diabetic retinopathy, the leading cause of blindness worldwide. Retina image fusion provides a practical way for determination of the oxygenation status of the ocular fundus. Such method would be a valuable medical diagnostic tool for diabetic retinopathy [14], age-related macular degeneration, glaucoma [15], retinopathy of prematurity, and central retinal vein occlusion [16].

### **4.1 Acquisition of retinal images**

Retinal images presented in this chapter were taken by a modified Topcon TRC-50EX fundus camera, with a lens and a c-mount through the vertical path of the camera. Hyperspectral images were taken through the vertical viewing port by an imaging

The Smith-Waterman algorithm was first published by Temple Smith and Michael Waterman in 1981 [13]. It is a well-known dynamic programming algorithm for local amino acid or nucleotide sequence alignment. Unlike the global alignment, the Smith-Waterman algorithm performs comparison among segments of all lengths and optimizes the similarity. It is guaranteed to find the optimal local alignment with respect to the scoring method. However, the Smith-Waterman algorithm requires *O(mn)* (m and n are the length of two input sequences) . In practical use, it has been replaced by the heuristic BLAST algorithm, which is much more efficient although not guaranteed to find the optimal alignments. The following output was from local alignment of the amino acid sequences of mouse's and

**3.4.2 Local alignment** 

[16].

**4.1 Acquisition of retinal images** 

human's using the Smith-Waterman algorithm.

**4. Diabetic retinopathy study through retinal image fusion** 

Hypoxia of the retina is believed to be a factor in the development of diabetic retinopathy, the leading cause of blindness worldwide. Retina image fusion provides a practical way for determination of the oxygenation status of the ocular fundus. Such method would be a valuable medical diagnostic tool for diabetic retinopathy [14], age-related macular degeneration, glaucoma [15], retinopathy of prematurity, and central retinal vein occlusion

Retinal images presented in this chapter were taken by a modified Topcon TRC-50EX fundus camera, with a lens and a c-mount through the vertical path of the camera. Hyperspectral images were taken through the vertical viewing port by an imaging spectrograph and digital camera (model VNIR 100; Photon Industries Inc., Mississippi Stennis Space Center, USA) across the fundus image (Figure 17).

The subjects of the retinal images were Cynomolgus monkeys of 4 to 4.5 years of age and 2.5 to 3 kg body weight with normal eyes [17]. The use of animals for taking retinal images was approved by Louisiana State University Health Sciences Center Institutional Animal Care and Use Committee [18]. This animal usage is also conformed to the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. The monkeys were housed in an air conditioned room with normal temperature and humidity with a 12 hour light-dark diurnal cycle.

Fig. 17. Hyperspectral imaging system in relation to the fundus camera. The image is redirected upward by a mirror. The imaging system is translated over the camera port by a linear actuator mounted below the imaging spectrograph and CCD camera [17].
