We started building a 3D digital map of the entire fruit fly brain, generating a huge amount of 3D image data and then doing the association image mining. These projects got us interested in the fruit fly’s nervous system, where cells’ identities are well-defined and where we could study how neurons are connected throughout the brain. We participated in several projects to measure gene expression in the fruit fly embryo and C. The data sets were mostly two-dimensional, and we realized that we really needed 3D data for gene expression. How have you applied your image analysis tools?īefore I arrived at Janelia, I worked on mapping gene expression in the fruit fly embryo. Then we produce quantitative measurements for the objects in the image to compare their various dimensions and look for patterns. We normalize objects so that they can be compared to each other directly. How do you compare their intrinsic features? You might compare the size of the head or their body with respect to their overall height. First, we standardize the data into a space so that we can directly compare all these objects. Once we have the objects, we need to find associations among the objects-for example, which neuron connects to which other neurons. How do they define a cell, a neuron? How do they describe the cell population? We use their definitions to train our computer to recognize objects and help scientists do this large-scale, complicated job automatically. We start there and consider the biologists’ knowledge. We call this automated process “image mining.”Ĭan you walk us through how you sift through the data?įirst, you need to define the meaningful objects or patterns.
In 3D microscopy, we let the computer pick out interesting objects, like particular neurons, and find the association between the cells, such as the potential connectivity between neurons.
It’s not just doing it faster we have to come up with whole new ways to process data that are meaningful for biology. Therefore, we need to design a smarter way to deal with those data. Confocal microscopes, for instance, can produce images with 1,000 or 10,000 times more pixels than an ordinary picture taken with an ordinary camera.ĭata sets are often so large, and the incoming speed of new data is so much faster than the processing speed, that you’ll never be able to process the data manually. With a 3D image, you’re going to have a lot of data. In the last 20 years, scientists and engineers have come up with super-powerful imaging systems to visualize the three-dimensional (3D) structure of a sample. How do you help biologists make sense of images? Peng’s toolkit might someday even help the Federal Reserve. Right now, his focus is the brain’s wiring. Now, at the Janelia Farm Research Campus, he is a leader in developing sophisticated ways to make sense of biological images. It has been designed to specifically work with mobile devices only.Even when he launched his career as an engineer and computer scientist, Hanchuan Peng was drawn to the beauty of biology. The SmartScope iGO is not compatible with PCs or Apple Mac. An existing wireless network or internet connection is NOT required.
Please note: iGo creates its own Wi-Fi network. Operational Range: 10 meters from a Wi-Fi connected device (outdoors).Support Protocol: 2.4GHz WiFi IEEE802.11b/g/n.
SMARTSCOPE DIGITAL MICROSCOPE SOFTWARE
SMARTSCOPE DIGITAL MICROSCOPE ANDROID
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