rrmaram2000
@rrmaram2000
Public Skills
matlab-medical-imaging-toolbox
by rrmaram2000
"MATLAB Medical Imaging Toolbox. Functions - medicalVolume, dicomread, dicominfo, dicomCollection, niftiread, niftiinfo, nrrdread, medicalref3d, intrinsicToWorld, worldToIntrinsic, volshow, sliceViewer, imregmoment, imregdeform, imregtform, radiomics, intensityFeatures, shapeFeatures, textureFeatures, medicalSegmentAnythingModel, segmentCells2D, dicomConnection, dicomquery, dicomget. Tasks - load medical scans, read DICOM series, open NIfTI or NRRD files, convert patient and voxel coordinates, visualize 3D volumes, overlay segmentation, align MRI or CT scans, register pre and post treatment images, extract radiomics features, segment with MedSAM or Cellpose, connect to PACS server, label ground truth, resample to isotropic spacing. Domains - DICOM, NIfTI, NRRD, MRI, CT, PET, PET/CT fusion, ultrasound, X-ray, brain imaging, liver segmentation, cardiac imaging, lung nodules, tumor analysis, clinical workflows, PACS integration."
matlab-stats-ml
by rrmaram2000
"MATLAB Statistics and Machine Learning Toolbox. Functions - fitcsvm, fitctree, fitcensemble, fitcknn, fitcnb, fitcnet, fitlm, fitglm, fitrgp, fitrensemble, lasso, kmeans, linkage, fitgmdist, dbscan, pca, tsne, factoran, ttest, ttest2, anova1, anovan, ranksum, chi2gof, fitdist, makedist, mle, ecdf, coxphfit, cvpartition, crossval, kfoldLoss, perfcurve, confusionchart, bayesopt, shapley, normalize. Tasks - run t-test or ANOVA, fit distributions, classify patients, train SVM or random forest, predict with regression, cluster data, reduce dimensions with PCA or t-SNE, cross-validate, compute ROC and AUC, select features, optimize hyperparameters, analyze survival data, plot Kaplan-Meier curves, handle missing data, interpret with SHAP or LIME. Domains - biomarker discovery, clinical trials, patient outcome prediction, diagnostic classification, gene expression, proteomics, epidemiology, survival analysis, treatment comparison."
matlab-image-processing-toolbox
by rrmaram2000
"MATLAB Image Processing Toolbox. Functions - imgaussfilt, medfilt2, wiener2, imfilter, graythresh, imbinarize, multithresh, watershed, activecontour, strel, imopen, imclose, imerode, imdilate, bwareaopen, imfill, regionprops, bwconncomp, bwlabel, edge, im2double, im2uint8, mat2gray, adapthisteq, imadjust, blockproc. Tasks - remove noise from an image, filter a noisy image, smooth an image, enhance contrast, threshold an image, segment objects, separate touching objects, clean up a binary mask, fill holes in mask, remove small objects, count cells or particles, measure region properties like area and centroid, detect edges, convert image data types, preprocess images before deep learning, apply morphological operations, extract texture features, process large images in blocks. Domains - MRI preprocessing, CT windowing, X-ray enhancement, microscopy, histology, cell counting, stain normalization, fluorescence imaging, binary mask cleanup, image segmentation pipeline."
matlab-deep-learning
by rrmaram2000
"MATLAB Deep Learning Toolbox. Functions - trainNetwork, trainnet, trainingOptions, unetLayers, unet, deeplabv3plusLayers, deeplabv3plus, semanticseg, yolov4ObjectDetector, fasterRCNNObjectDetector, maskrcnn, resnet50, vgg16, efficientnetb0, dlarray, dlfeval, dlgradient, adamupdate, dlnetwork, imageDatastore, augmentedImageDatastore, minibatchqueue. Tasks - train a deep learning model, classify medical images, build a CNN classifier, segment tumors or organs, detect objects or nodules in images, fine-tune a pretrained network, set up transfer learning, create a U-Net for segmentation, train with custom loss function, augment training data, deploy model to ONNX, run training on GPU, build a 3D volumetric network, compare model architectures, improve training accuracy, reduce overfitting, handle class imbalance. Domains - MRI, CT, X-ray, PET, histopathology, dermatology, retinal imaging, cell detection, medical image classification, lesion segmentation, nodule detection, pathology grading."
matlab-wavelet-toolbox
by rrmaram2000
"MATLAB Wavelet Toolbox. Functions - wavedec2, waverec2, dwt2, idwt2, swt2, lwt2, ilwt2, wdenoise2, dualtree2, idualtree2, shearletSystem, liftingScheme, liftingStep, addlift, wfilters, wmaxlev, dldwt, dlidwt, cwtLayer, appcoef2, detcoef2. Tasks - decompose an image into frequency bands, denoise a medical image using wavelets, remove noise from MRI or CT or ultrasound, extract texture features at multiple scales, design a custom wavelet, learn wavelets from data, detect edges and orientations, analyze directional structures like vessels or fibers, fuse multi-modal images, compress an image with wavelets, build wavelet layers for deep learning, choose the right wavelet for my image type, verify perfect reconstruction. Domains - MRI denoising, CT noise reduction, ultrasound speckle removal, Rician noise, Poisson noise, multiresolution analysis, image fusion, texture classification, vessel detection, fiber analysis, wavelet-based feature extraction, medical image preprocessing."