(These 20 images are stored in 20 DICOM files with names such as brain_017.dcm, which you can download from MATLAB Central if you want to run the examples.) Let's suppose we know that each image is 256-by-256 and contains signed 16-bit data. Suppose that we have a study consisting of a series of 20 transverse MRI brain images and we want to read them into MATLAB. Each series is performed on a single modality such as an MR, CT, or X-ray device and can have multiple related images. In medical imaging, a patient is subject to an imaging study, which may contain multiple series of images. Software such as MATLAB that supports DICOM can share images with all of these devices, provided that each of the hardware devices has implemented the necessary DICOM services. Integration isn't limited to just hardware. For example, it is possible to integrate a MR scanner from GE Medical Systems with a picture archive system (PACS) from Agfa and another vendor's film printer without using translation devices. DICOM is the common format, easing integration of solutions from different vendors. With the advent of DICOM as a formal standard in 1993, one protocol replaced many protocols and formats. A cottage industry developed to provide data translation services. This process was chaotic and fraught with difficulty. Integrating medical hardware and software from different vendors meant translating from one vendor's protocols to another's. Before DICOM, each manufacturer used proprietary image formats and communications protocols to connect their hardware solutions with third-party products. DICOM has significantly improved communication between medical devices and lowered the cost and complexity of integrating hardware and software solutions.
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