Corneal confocal microscopy (CCM) is a fast and non-invasive method used in ophthalmology to capture images of the cornea. The segmentation and morphometric evaluation of corneal sub-basal
nerves in corneal confocal microscopy images have garnered growing attention in recent times. This attention stems from the potential application of alterations in these nerves as a straightforward and non-invasive
approach for the early detection and monitoring of peripheral diabetic neuropathy, a significant contributor
to long-term health issues in individuals with diabetes. We are trying to modify a novel curvilinear structure
segmentation network known as CS2
-Ne
2. • Corneal confocal microscopy (CCM) is a fast and non-invasive method
used in ophthalmology to capture images of the cornea. The
segmentation and morphometric evaluation of corneal sub-basal
nerves in corneal confocal microscopy images have garnered growing
attention in recent times.
3. • Introduction The objective of medical image segmentation is to
enhance the clarity of anatomical or pathological changes within
images. This process often plays a pivotal role in computer-aided
diagnosis and advanced medical practices, significantly improving
diagnostic precision and efficiency. Notable tasks in medical image
segmentation encompass the delineation of structures such as the
corneal nerve and fiber, brain and brain tumors [3] , liver and liver
tumors [7], lung structures including pulmonary nodules [10] the
optic disc, cellular structures and cardiac image segmentation
4. • Petal and sepal width and length measurements performed on iris
flowers for the purpose of data classification. The image shown is of
the Iris virginica gender.
• Petal and sepal width and length measurements performed on iris
flowers for the purpose of data classification. The image shown is of the
Iris virginica gender.
x1 = Petal width
x2 = Petal length
x3 = Sepal width
x4 = Sepal length
5. Dataset The CORN (Corneal Nerve Database) is a collection of datasets intended
solely for academic research purposes. CORN-1 consists of 1698 CCM images of
the corneal subbasal epithelium, captured using a Heidelberg Retina Tomograph
with a Rostock Cornea Module microscope.
