Researchers at Harvard University and MIT have come up with an easy way to 3D print highly detailed models of human brains in less than an hour – for a fraction of the cost and labor needed for a lower quality product.
In theory, medical imaging technologies like MRI and CT scans produce high-resolution images as a series of ‘slices,’ making them an obvious complement to 3D printers, which also print in slices. But as MIT graduate Steven Keating found when he wanted to examine his own brain following his surgery to remove a baseball-sized tumour, the existing methods were prohibitively time-intensive, cumbersome, and failed to accurately reveal important features of interest.
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Keating collaborated with a team of scientists, including James Weaver, PhD, a senior research scientist at the Wyss Institute; Neri Oxman, Ph.D., Director of the MIT Media Lab’s Mediated Matter group and Associate Professor of Media Arts and Sciences to devleop a new technique that allows images from MRI and CT scans to be easily and quickly converted into physical models with unprecedented detail.
The new method offers a fast and highly accurate method for converting complex images into a format that can be easily 3D printed. The key lies in printing with dithered bitmaps, a digital file format in which each pixel of a grayscale image is converted into a series of black and white pixels, and the density of the black pixels is what defines the different shades of gray rather than the pixels themselves varying in color.
Similar to the way images in black-and-white newsprint use varying sizes of black ink dots to convey shading, the more black pixels that are present in a given area, the darker it appears. By simplifying all pixels from various shades of gray into a mixture of black or white pixels, dithered bitmaps allow a 3D printer to print complex medical images using two different materials that preserve all the subtle variations of the original data with much greater accuracy and speed.
The team of researchers used bitmap-based 3D printing to create models of Keating’s brain and tumor that faithfully preserved all of the gradations of detail present in the raw MRI data down to a resolution that is on par with what the human eye can distinguish from about 9-10 inches away. Using this same approach, they were also able to print a variable stiffness model of a human heart valve using different materials for the valve tissue versus the mineral plaques that had formed within the valve, resulting in a model that exhibited mechanical property gradients and provided new insights into the actual effects of the plaques on valve function.
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