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pcregistericp matlab functions  (MathWorks Inc)


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    MathWorks Inc pcregistericp matlab functions
    FIGURE 2 Workflow of the <t>MATLAB</t> program for active marrow dose calculation of radiotherapy patients.
    Pcregistericp Matlab Functions, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 409 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/pcregistericp+function+of/Computer+Vision+Toolbox/pm38734989-47-12-13
    Average 96 stars, based on 409 article reviews
    pcregistericp matlab functions - by Bioz Stars, 2026-11
    96/100 stars

    Images

    1) Product Images from "A novel method for rapid estimation of active bone marrow dose for radiotherapy patients in epidemiological studies."

    Article Title: A novel method for rapid estimation of active bone marrow dose for radiotherapy patients in epidemiological studies.

    Journal: Medical physics

    doi: 10.1002/mp.17118

    FIGURE 2 Workflow of the MATLAB program for active marrow dose calculation of radiotherapy patients.
    Figure Legend Snippet: FIGURE 2 Workflow of the MATLAB program for active marrow dose calculation of radiotherapy patients.

    Techniques Used:

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    Article Snippet: Development and within-batch evaluation of the segmentation component (a) Segmentation model and training A convolutional encoder–decoder network was implemented in MATLAB R2024a using the Deep Learning Toolbox and Computer Vision Toolbox.

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    Article Snippet: The Camera Calibrator app in MATLAB R2025b (Computer Vision Toolbox, version 25.2) was used with checkerboard images acquired at different positions and orientations.

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    Article Snippet: Following preprocessing, geometric calibration was performed using Zhang’s method [22] under a pinhole camera model, implemented in MATLAB R2025b using routines from the Computer Vision Toolbox.

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    Article Snippet: All analyses were performed using MATLAB 2024a and the Computer Vision Toolbox (MathWorks Inc., Natick, MA, USA).

    Software:

    Article Title: Contextual camera controls during a collaboration session in a heterogenous computing platform
    Article Snippet: .. Non-limiting examples of available AI algorithms, software, and libraries that may be utilized within embodiments of systems and methods described herein include, but are not limited to: PYTHON, OPENCV, INCEPTION, THEANO, TORCH, PYTORCH, PYLEARN2, NUMPY, BLOCKS, TENSORFLOW, MXNET, CAFFE, LASAGNE, KERAS, CHAINER, MATLAB Deep Learning, CNTK, MatConvNet (a MATLAB toolbox implementing convolutional neural networks for computer vision applications), DeepLearnToolbox (a Matlab toolbox for Deep Learning from Rasmus Berg Palm), BigDL, Cuda-Convnet (a fast C++/CUDA implementation of convolutional or feed-forward neural networks), Deep Belief Networks, RNNLM, RNNLIB-RNNLIB, matrbm, deeplearning4j, Eblearn.Ish, deepmat, MShadow, Matplotlib, SciPy, CXXNET, Nengo-Nengo, Eblearn, cudamat, Gnumpy, 3-way factored RBM and mcRBM, mPoT, ConvNet, ELEKTRONN, OpenNN, NEURALDESIGNER, Theano Generalized Hebbian Learning, Apache SINGA, Lightnet, and SimpleDNN. ..

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    Article Snippet: Such AI/ML model(s) may implement: a neural network (e.g., artificial neural network, deep neural network, convolutional neural network, recurrent neural network, autoencoders, reinforcement learning, etc.), fuzzy logic, deep learning, deep structured learning hierarchical learning, Support Vector Machine (SVM) (e.g., linear SVM, nonlinear SVM, SVM regression, etc.), decision tree learning (e.g., classification and regression tree or “CART”), Very Fast Decision Tree (VFDT), ensemble methods (e.g., ensemble learning, Random Forests, Bagging and Pasting, Patches and Subspaces, Boosting, Stacking, etc.), dimensionality reduction (e.g., Projection, Manifold Learning, Principal Components Analysis, etc.), or the like. .. Non-limiting examples of available AI/ML algorithms, models, software, and libraries that may be utilized within embodiments of systems and methods described herein include, but are not limited to: PYTHON, OPENCV, INCEPTION, THEANO, TORCH, PYTORCH, PYLEARN2, NUMPY, BLOCKS, TENSORFLOW, MXNET, CAFFE, LASAGNE, KERAS, CHAINER, MATLAB Deep Learning, CNTK, MatConvNet (a MATLAB toolbox implementing convolutional neural networks for computer vision applications), DeepLearnToolbox (a Matlab toolbox for Deep Learning from Rasmus Berg Palm), BigDL, Cuda-Convnet (a fast C++/CUDA implementation of convolutional or feed-forward neural networks), Deep Belief Networks, RNNLM, RNNLIB-RNNLIB, matrbm, deeplearning4j, Eblearn.lsh, deepmat, MShadow, Matplotlib, SciPy, CXXNET, Nengo-Nengo, Eblearn, cudamat, Gnumpy, 3-way factored RBM and mcRBM, mPOT, ConvNet, ELEKTRONN, OpenNN, NEURALDESIGNER, Theano Generalized Hebbian Learning, Apache SINGA, Lightnet, and SimpleDNN. ..

    Article Title: Systems and methods for remotely provisioning facial recognition data to heterogeneous computing platforms
    Article Snippet: .. Non-limiting examples of software and libraries which may be utilized within embodiments of systems and methods described herein to perform AI modeling operations include, but are not limited to: PYTHON, OPENCV, scikit-learn, INCEPTION, THEANO, TORCH, PYTORCH, PYLEARN2, NUMPY, BLOCKS, TENSORFLOW, MXNET, CAFFE, LASAGNE, KERAS, CHAINER, MATLAB Deep Learning, CNTK, MatConvNet (a MATLAB toolbox implementing convolutional neural networks for computer vision applications), DeepLearnToolbox (a Matlab toolbox for Deep Learning from Rasmus Berg Palm), BigDL, Cuda-Convnet (a fast C++/CUDA implementation of convolutional or feed-forward neural networks), Deep Belief Networks, RNNLM, RNNLIB-RNNLIB, matrbm, deeplearning4j, Eblearn.lsh, deepmat, MShadow, Matplotlib, SciPy, CXXNET, Nengo-Nengo, Eblearn, cudamat, Gnumpy, 3-way factored RBM and mcRBM, mPoT, ConvNet, ELEKTRONN, OpenNN, NEURALDESIGNER, Theano Generalized Hebbian Learning, Apache SINGA, Lightnet, and SimpleDNN. ..



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    Image Search Results


    FIGURE 2 Workflow of the MATLAB program for active marrow dose calculation of radiotherapy patients.

    Journal: Medical physics

    Article Title: A novel method for rapid estimation of active bone marrow dose for radiotherapy patients in epidemiological studies.

    doi: 10.1002/mp.17118

    Figure Lengend Snippet: FIGURE 2 Workflow of the MATLAB program for active marrow dose calculation of radiotherapy patients.

    Article Snippet: The downsampling and ICP algorithm were implemented by using the pcdownsample and pcregistericp MATLAB functions (available in Computer Vision ToolboxTM).

    Techniques:

    Matching of the 3D segmentation obtained from the cadaver’s head CT scan and the data obtained from manual scanning of the cadaver’s head forehead and nose skin using an EM sensor using the pcregistericp() function of Matlab. ( a ) frontal view; ( b ) lateral view; ( c ) top view.

    Journal: Scientific Reports

    Article Title: A miniature robotic steerable endoscope for maxillary sinus surgery called PliENT

    doi: 10.1038/s41598-022-05969-3

    Figure Lengend Snippet: Matching of the 3D segmentation obtained from the cadaver’s head CT scan and the data obtained from manual scanning of the cadaver’s head forehead and nose skin using an EM sensor using the pcregistericp() function of Matlab. ( a ) frontal view; ( b ) lateral view; ( c ) top view.

    Article Snippet: The transformation matrix between the point cloud and the data acquired from the EM sensor was found using the pcregistericp() function of Matlab (MathWorks, Massachusetts, USA), which register two point clouds using an ICP algorithm.

    Techniques: Computed Tomography