6515--Digital Non-Mydriatic Retinal Camera
250-NETWORK CONTRACT OFFICE 10 (36C250)
Digital Non-Mydriatic Fundus Camera System This announcement requests information from industry to support market research and preliminary acquisition planning for the procurement of (1) one digital non-mydriatic fundus camera system with retinal image-capture software and vendor installation for the new East Indianapolis VA Clinic Tele-Eye Screening room. Of particular interest is identifying products that are made in America and meet the domestic end-product test of FAR 25.101. This is not a solicitation for proposals. No contract will be awarded from this notice. REQUIREMENT The agency is seeking information on sources of supply for one digital non-mydriatic fundus camera system with retinal image-capture software. Description: Compact, non-mydriatic digital retinal imaging system designed to acquire high-resolution color and fundus autofluorescence images of the human retina. The system shall support screening, documentation, and monitoring of ocular conditions without routinely requiring pharmacological pupil dilation. Salient Characteristics: Shall provide color retinal photography and fundus autofluorescence imaging. Shall produce retinal images with a resolution of at least 32 megapixels. Shall use infrared light for patient alignment and focusing before image capture. Shall acquire images through pupils approximately 3.3 mm in diameter or smaller without routinely requiring dilation. Shall provide automated alignment, focusing, exposure adjustment, image capture, and switching between anterior-eye and retinal observation. Shall permit the operator to override automatic focusing and manually adjust focus when necessary. Shall automatically evaluate image focus and eye alignment and alert the operator when image quality is insufficient. Shall provide digital image-processing modes capable of emphasizing retinal vascular and structural features, including red-free and blue-spectrum viewing modes. Shall include contrast-enhancement processing to improve differe
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