Abstract: Eyes are considered to be the most sensitive and
important organ for human being. Thus, any eye disorder will affect
the patient in all aspects of life. Cataract is one of those eye disorders
that lead to blindness if not treated correctly and quickly. This paper
demonstrates a model for automatic detection, classification, and
grading of cataracts based on image processing techniques and
artificial intelligence. The proposed system is developed to ease the
cataract diagnosis process for both ophthalmologists and patients.
The wavelet transform combined with 2D Log Gabor Wavelet
transform was used as feature extraction techniques for a dataset of
120 eye images followed by a classification process that classified the
image set into three classes; normal, early, and advanced stage. A
comparison between the two used classifiers, the support vector
machine SVM and the artificial neural network ANN were done for
the same dataset of 120 eye images. It was concluded that SVM gave
better results than ANN. SVM success rate result was 96.8%
accuracy where ANN success rate result was 92.3% accuracy.
Abstract: This paper presents design and characterization of a
microaccelerometer designated for integration into cataract surgical
probe to detect hardness of different eye tissues during cataract
surgery. Soft posterior lens capsule of eye can be easily damaged in
comparison with hard opaque lens since the surgeon can not see
directly behind cutting needle during the surgery. Presence of
microsensor helps the surgeon to avoid rupturing posterior lens
capsule which if occurs leads to severe complications such as
glaucoma, infection, or even blindness. The microsensor having
overall dimensions of 480 μm x 395 μm is able to deliver significant
capacitance variations during encountered vibration situations which
makes it capable to distinguish between different types of tissue.
Integration of electronic components on chip ensures high level of
reliability and noise immunity while minimizes space and power
requirements. Physical characteristics and results on performance
testing, proves integration of microsensor as an effective tool to aid
the surgeon during this procedure.