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Medical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care.
Image registration or image alignment algorithms can be classified into intensity-based and feature-based. [3] One of the images is referred to as the moving or source and the others are referred to as the target, fixed or sensed images. Image registration involves spatially transforming the source/moving image(s) to align with the target image.
An MIT-led research team has crafted a machine learning algorithm that can analyze 3D scans up to 1,000 times faster than before, making it possible to study changes almost in real time -- less ...
The regularization parameter plays a critical role in the denoising process. When =, there is no smoothing and the result is the same as minimizing the sum of squares.As , however, the total variation term plays an increasingly strong role, which forces the result to have smaller total variation, at the expense of being less like the input (noisy) signal.
Computational imaging systems span a broad range of applications. While applications such as SAR, computed tomography, seismic inversion are well known, they have undergone significant improvements (faster, higher-resolution, lower dose exposures [3]) driven by advances in signal and image processing algorithms (including compressed sensing techniques), and faster computing platforms.
If the goal is a medical diagnostic, then histology applications will often fall into the realm of digital pathology or automated tissue image analysis, which are sister fields of bioimage informatics. The same computational techniques are often applicable, but the goals are medically- rather than research-oriented.
MITK, the Medical Imaging Interaction Toolkit is an open source project for developing interactive medical image processing software, developed at the Deutsche Krebsforschungszentrum, Heidelberg Voreen , an open source, multi-platform volume rendering engine, maintained by the Visualization and Computer Graphics Research Group (VisCG) at the ...
An excellent overview can be found in the special issue [5] of IEEE Transaction on Medical Imaging. One group of deep learning reconstruction algorithms apply post-processing neural networks to achieve image-to-image reconstruction, where input images are reconstructed by conventional reconstruction methods.