Automatic segmentation and quantified analysis of meibomian glands from infrared images.

Purpose: An algorithm for automated segmentation of meibomian glands from infrared images obtained using a novel prototype infrared hand-held imager has been proposed in this study. Meibomian gland dysfunction (MGD) is quantified in terms of five clinically relevant metrics. A comparison of these metrics in patients with MGD has been presented against a sample of the normative healthy population. Methods: This is a prospective cross-sectional observational study. Patients presenting to the clinics were enrolled after written informed consent. The everted eyelids of 200 eyes of patients (of which 100 were healthy and 100 were diagnosed with MGD) were imaged using a prototype hand-held camera. The proposed algorithm was used to process the images using enhancement techniques and the glands were automatically segmented. A comparison of glands of normal eyes versus MGD-affected eyes is performed using five metrics presented in this study: (i) drop-out, (ii) length, (iii) width, (iv) the number of glands, and (v) the number of tortuous glands. Results: The 95% confidence interval for the metrics did not show any overlap between the two groups. In MGD patients, the drop-out ratio was higher than normal. The length and number of glands were significantly lesser than normal. A number of tortuous glands were more in the MGD group. The metrics for MGD versus healthy and cut-off ranges were computed in the results. Conclusion: The prototype infrared hand-held meibographer and the proposed automatic algorithm for gland segmentation and quantification are effective aids in MGD diagnosis. We present a set of five metrics, which are clinically relevant for guiding clinicians in the diagnosis of MGD.

Ratio images and ultraviolet C excitation in autofluorescence imaging of neoplasms of the human colon.

The accepted screening technique for colon cancer is white light endoscopy. While most abnormal growths (lesions) are detected by this method, a significant number are missed during colonoscopy, potentially resulting in advanced disease. Missed lesions are often flat and inconspicuous in color. A prototype ultraviolet spectral imager measuring autofluorescence (AF) and reflectance has been developed and applied in a study of 21 fresh human colon surgical specimens. Six excitation wavelengths from 280 to 440 nm and formulaic ratio imaging were utilized to increase lesion contrast and cause neoplasms to appear bright compared to normal tissue. It was found that in the subset of lesions which were most difficult to visualize in standard color photographs [low contrast lesions, (LCLs)] a ratio image (F340/F440) of AF images excited at 340 and 440 nm produced extraordinary images and was effective in about 70% of these difficult cases. Contrast may be due to increased levels of reduced nicotinamide adenine dinucleotide, increased hemoglobin absorption, and reduced signal from submucosal collagen. A second successful ratio image (R480/R555) combined two reflectance images to produce exceptional images especially in particular LCLs where F340/F440 was ineffective. The newly discovered ratio images can potentially improve detection rate in screening with a novel AF colonoscope.

Tryptophan autofluorescence imaging of neoplasms of the human colon.

Detection of flat neoplasia is a major challenge in colorectal cancer screening, as missed lesions can lead to the development of an unexpected 'incident' cancer prior to the subsequent endoscopy. The use of a tryptophan-related autofluorescence has been reported to be increased in murine intestinal dysplasia. The emission spectra of cells isolated from human adenocarcinoma and normal mucosa of the colon were studied and showed markedly greater emission intensity from cancerous cells compared to cells obtained from the surrounding normal mucosa. A proto-type multispectral imaging system optimized for ultraviolet macroscopic imaging of tissue was used to obtain autofluorescence images of surgical specimens of colonic neoplasms and normal mucosa after resection. Fluorescence images did not display the expected greater emission from the tumor as compared to the normal mucosa, most probably due to increased optical absorption and scattering in the tumors. Increased fluorescence intensity in neoplasms was observed however, once fluorescence images were corrected using reflectance images. Tryptophan fluorescence alone may be useful in differentiating normal and cancerous cells, while in tissues its autofluorescence image divided by green reflectance may be useful in displaying neoplasms.