prazg
PhD Candidate in Cancer Imaging/Radiogenomics in Glioblastoma @KCL-BMEIS; Senior Registrar in Neurosurgery at King's College Hospital, London
@KCL-BMEISLondon, UK
Pinned Repositories
combat_RNA
Python code for running pycombat library to harmonise gene level fpkm values from RNA seq data
cptac
Python packaging for CPTAC data
Deep-Features-Nifti-Network-DEN
This repository defines a Convolutional Neural Network (CNN) model that extracts deep features from Nifti MRI files of segmented glioblastoma tumours
DicomData
This repository provides you with python code snippet on extracting Metadata of Dicom files including Magnetic field strength, study date and manufacturer.
ecotyper
EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.
gbm-data-longitudinal
This repository contains code used to prepare the LUMIERE Glioblastoma dataset.
GBMDeconvoluteR
A Deconvolution Tool For Glioblastoma (GBM) Datasets
HD-BET
Automated deep-learning based brain extraction applicable to a broad range of MRI sequence types and with robust performance even in the presence of pathology or treatment-induced tissue alterations.
HD-GLIO
Automated deep-learning based brain tumor segmentation on MRI
Metadata_Bam
This is a library of codes for extracting and saving metadata obtained from a aligned BAM file.
prazg's Repositories
prazg/HD-GLIO
Automated deep-learning based brain tumor segmentation on MRI
prazg/combat_RNA
Python code for running pycombat library to harmonise gene level fpkm values from RNA seq data
prazg/cptac
Python packaging for CPTAC data
prazg/Deep-Features-Nifti-Network-DEN
This repository defines a Convolutional Neural Network (CNN) model that extracts deep features from Nifti MRI files of segmented glioblastoma tumours
prazg/DicomData
This repository provides you with python code snippet on extracting Metadata of Dicom files including Magnetic field strength, study date and manufacturer.
prazg/ecotyper
EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.
prazg/gbm-data-longitudinal
This repository contains code used to prepare the LUMIERE Glioblastoma dataset.
prazg/GBMDeconvoluteR
A Deconvolution Tool For Glioblastoma (GBM) Datasets
prazg/HD-BET
Automated deep-learning based brain extraction applicable to a broad range of MRI sequence types and with robust performance even in the presence of pathology or treatment-induced tissue alterations.
prazg/Metadata_Bam
This is a library of codes for extracting and saving metadata obtained from a aligned BAM file.
prazg/neuroCombat_Radiomics
This repository provides code in jupyter notebook on application of neuroCombat package for radiomics data extracted from segmented MRI brain images
prazg/nnUNet
prazg/PCA_radiomics
Principal Component Analysis (PCA) on a dataset of radiomics features
prazg/pyradiomics
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics
prazg/TcellExTRECT
prazg/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
prazg/TractSeg
Automatic White Matter Bundle Segmentation
prazg/Unstranded-to-Gene_level-FPKM
This repository has python code within Jupyter Notebook to convert unstranded fpkm values of RNA sequecing data to stranded fpkm values and then to gene-level fpkm values to standardize the data obtained from multiple datasets
prazg/xCell
Cell types enrichment analysis