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Once the Navy user answers those questions, the software immediately learns from the experience so that it becomes better at spotting mines.

To illustrate how the software works, Stack paints the scenario of a sailor viewing sonar imagery in search of threats. The active-learning software spots an object it has never seen before, something that may or may not be a mine. A message box pops open, querying the user about the nature of the object, and if the user chooses to label the item as either a mine or something other than a mine, the software learns what it is and will not need to ask the next time.

Doctors, meanwhile, face a similar problem: identifying specific cells in human tissue. Physicians sometimes must view hundreds of microscopic images containing millions of cells. It can take weeks for a pathologist to manually pinpoint cells in images. Identifying cells is critical to a proper diagnosis and treatment. But diagnosing the specific type of cancer can be challenging, making treatment more difficult. Knowing the type of cancer allows doctors to use targeted therapy and to have an actual understanding of the prognosis, Roysam says.

That is not only expensive but possibly harmful because it can have side effects. And it totally depends on who is using the tool and how they were trained. Training includes providing a data set, such as a host of cell samples with corresponding labels indicating whether or not the cells are cancerous. Navy explosive ordnance disposal diver attaches an inert charge to a training mine during exercises near the naval base in Guantanamo Bay, Cuba.

Surrounding Area Directions Drive Time. General Description minimize. MLS :. Tarrant County. Selling Agent and Brokerage minimize. Selling Agent. Selling Broker. Property Tax minimize. Market Value Per Appraisal District. Schools minimize. Property Map minimize. Nearby Places. Drive Time. Importantly, all modules are accessible through the Python scripting language which allows users to create scripts to accomplish sophisticated associative image analysis tasks over multi-dimensional microscopy image data.

In the past years the software has evolved so that it can be used routinely to analyze high throughput high content image data. Core modules like segmentation, tracing, and tracking have been updated to handle images of the order of hundreds of gigabytes efficiently.

Also, the graphical user interface has been updated to efficiently visualize and more importantly edit these huge datasets. In particular, three projects will be presented to the audience: the study of immune system response to the implantation of neuroprostetic devices, the study of high-throughput immune cell interaction, and the profiling of cell population changes. Email Address.