Citation: Pardue MT, Barnes CS, Kim MK, et al. Rodent hyperglycemiainduced inner retinal defects are mirrored in human diabetes. Tran Vis Sci Tech. 2014;3(3):6, http:// tvstjournal.org/doi/full/10. 1167/tvst. 3.3.6, doi:10.1167/tvst.3.3.6 Purpose: To evaluate the utility of low luminance stimuli to functionally probe inner retinal rod pathways in the context of diabetes mellitus in both rat and human subjects.Methods: Inner retinal dysfunction was assessed using oscillatory potential (OP) delays in diabetic rats. Scotopic electroretinograms (ERGs) in response to a series of increasing flash luminances were recorded from streptozotocin (STZ)-treated and control Sprague-Dawley rats after 7, 14, 20, and 29 weeks of hyperglycemia. We then evaluated OP delays in human diabetic subjects with (DR) and without (DM) diabetic retinopathy using the International Society for Clinical Electrophysiology in Vision (ISCEV) standard scotopic protocol and two additional dim test flashes.Results: Beginning 7 weeks after STZ, OP implicit times in diabetic rats were progressively delayed in response to dim, but not bright stimuli. In many diabetic subjects the standard ISCEV dim flash failed to illicit measureable OPs. However, OPs became measurable using a brighter, nonstandard dim flash (Test Flash 1, À1.43 log cd s/m 2 ), and exhibited prolonged implicit times in the DM group compared with control subjects (CTRL).Conclusions: Delays in scotopic OP implicit times are an early response to hyperglycemia in diabetic rats. A similar, inner retinal, rod-driven response was detected in diabetic human subjects without diabetic retinopathy, only when a nonstandard ISCEV flash intensity was employed during ERG testing.Translational Relevance: The addition of a dim stimulus to standard ISCEV flashes with assessment of OP latency during ERG testing may provide a detection method for early retinal dysfunction in diabetic patients.

Locating region of interest for breast cancer masses in the mammographic image is a challenging problem in medical image processing. In this research work, the keen idea is to efficiently extract suspected mass region for further examination. In particular to this fact breast boundary segmentation on sliced rgb image using modified intensity based approach followed by quad tree based division to spot out suspicious area are proposed in the paper. To evaluate the performance DDSM standard dataset are experimented and achieved acceptable accuracy.

In this research work, we perform text line segmentation directly in compressed representation of an unconstraint handwritten document image using tunneling algorithm. In this relation, we make use of text line terminal point which is the current state-of-the-art that enables text line segmentation. The terminal points spotted along both margins (left and right) of a document image for every text line are considered as source and target respectively. The effort in spotting the terminal positions is performed directly in the compressed domain. The tunneling algorithm uses a single agent (or robot) to identify the coordinate positions in the compressed representation to perform text-line segmentation of the document. The agent starts at a source point and progressively tunnels a path routing in between two adjacent text lines and reaches the probable target. The agent's navigation path from source to the target bypassing obstacles, if any, results in segregating the two adjacent text lines. However, the target point would be known only when the agent reaches destination; this is applicable for all source points and henceforth we could analyze the correspondence between source and target nodes. In compressed representation of a document image, the continuous pixel values in a spatial domain are available in the form of batches known as whiteruns (background) and black-runs (foreground). These batches are considered as features of a document image represented in a Grid. Performing text-line segmentation using these features makes the system inexpensive when compared to spatial domain processing. Artificial Intelligence in Expert systems, dynamic programming and greedy strategies are employed for every search space while tunneling. An exhaustive experimentation is carried out on various benchmark datasets including ICDAR13 and the performances are reported.

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