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Machine Learning Applications In Medical Image Processing
Published in Sanjay Saxena, Sudip Paul, High-Performance Medical Image Processing, 2022
Tanmay Nath, Martin A. Lindquist
Finally, there are multiple free open-source software packages used for medical image processing. The most popular package for neuroimaging (including fMRI, PET, SPECT, EEG, and MEG processing) is statistical parametric mapping (SPM) [59], a MATLAB based toolbox that allows for end-to-end analysis. AFNI (analysis of functional neuroimages) [60] is another comprehensive package for analysis of anatomical and function MRI. It has many built-in functions written in C, Python, R, and shell scripts. Its installation files are zipped in a binary package which can be easily installed in any operating system (OS). FSL (FMRIB software library) [61] is another package that can be used to analyze fMRI, MRI, and DTI data. It is also written in C and consists of a series of programs for pre-processing, conducting statistical analysis, and visualizing the results. FreeSurfer [62] is another C based software package that studies the surface of brain, especially the cortical and sub-cortical anatomy using structural, functional MRI, DTI, and PET. 3D Slicer [63] is an open-source platform for medical image analysis (e.g., image registration and segmentation) across multiple modalities including MRI, CT, Ultrasound, nuclear medicine, and microscopy. Furthermore, there is a python-based pipeline namely Nipype (Neuroimaging in Python Pipelines and Interfaces) [64], which provides an interface to the above packages within a single framework. Thus, a user in Nipy (https://nipy.org/) can interactively explore algorithms from different packages and combine them to process data faster.
Quantitative imaging using CT
Published in Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin, Radiomics and Radiogenomics, 2019
Lin Lu, Lawrence H. Schwartz, Binsheng Zhao
3D Slicer and ITK-SNAP are two popular segmentation software packages that are publicly available. 3D Slicer is an open source software available for multiple operating systems, including Linux, MacOSX, and Windows. It is a platform that provides image analysis (e.g., registration and interactive segmentation) and visualization (e.g., volume rendering) of medical images including CT, MRI, and positron emission tomography (PET). ITK-SNAP [43] is an easy-to-use software tool that provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation.
GPU-based Medical Image Segmentation: Brain MRI Analysis Using 3D Slicer
Published in Mitul Kumar Ahirwal, Narendra D. Londhe, Anil Kumar, Artificial Intelligence Applications for Health Care, 2022
3D Slicer is an open-source software platform for medical image informatics, image processing, and three-dimensional visualization. Mainly written in C++ and based on the NA-MIC kit, 3D Slicer relies on a variety of libraries: VTK, ITK, CTK, CMake, Qt, and Python. 3D Slicer consists of both an application core, as well as having modules that offer specific functionality. The core implements the UI, data I/O, and visualization while exposing developer interfaces for the use of extensions with new modules.
A Systematic Review of Human–Computer Interaction (HCI) Research in Medical and Other Engineering Fields
Published in International Journal of Human–Computer Interaction, 2022
Alireza Sadeghi Milani, Aaron Cecil-Xavier, Avinash Gupta, J. Cecil, Shelia Kennison
Jefferson (2019) presented the initial outcomes of using an immersive VR-based preoperative planning tool for laparoscopic donor nephrectomy. The author stated that it was challenging to understand more than 2500 CT images hence they developed 3D models using a 3D slicer which allowed an interactive and comprehensive anatomy when viewed through an immersive headset. The CT images of seven patients were used for a study in which two surgeons assessed the preoperative understanding using CT alone and CT on the immersive headset. The results from the study indicated that immersive models enhanced the surgeons’ understanding of the patient’s arterial and venous anatomy. Moreover, the surgeons’ overall confidence regarding the operation improved while interacting with the 3D image on the immersive headset.
VentroAR: an augmented reality platform for ventriculostomy using the Microsoft HoloLens
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2023
Naghmeh Bagher Zadeh Ansari, Étienne Léger, Marta Kersten-Oertel
The proposed application uses 3D Slicer, an open-source software library with various tools and plugins for clinical and biomedical image computing applications. 3D Slicer was used to segment the head and ventricles and for receiving and sending transforms through OpenIGTLinkIF, Tokuda et al. (2009), module of SlicerIGT, Ungi et al. (2016). The Slicer-Atracsys connection is made using the PLUS Toolkit, Lasso et al. (2014), which provides live streaming and recording of pose tracking data.
Special Instructions: Information not found in special instruction field Fit of fire boots: Exploring internal morphology using computed tomography scan
Published in International Journal of Occupational Safety and Ergonomics, 2023
3D Slicer, an open-source software [30,31] for 3D visualization of the MRI and CT scan images was used for image processing in this study. The 3D models of the boots were exported in .obj format. A 3D graphic tool (Rhinoceros® version 6, Robert McNeel & Associates, USA) further processed and measured the boot models.