There are 1 repository under tumor topic.
DELLY2: Structural variant discovery by integrated paired-end and split-read analysis
EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.
Utilities to download and load an MRI brain tumor dataset with Python, providing 2D slices, tumor masks and tumor classes.
This repo has been archived, these workflows are still available in the GATK repository under the scripts directory. The workflows are also organized in Dockstore in the GATK Best Practices Workflows collection.
DeTiN is designed to measure tumor-in-normal contamination and improve somatic variant detection sensitivity when using a contaminated matched control.
a PyQt5 Implementation
Extract and evaluate radiomics for liver cancer tumors from DICOM segmentation masks. Using SimpleITK, PyRadiomics and PyDicom.
Code, data and model for Pérez-García et al. 2021, "A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections"
CaDRReS-Sc is a framework for analyzing drug response heterogeneity based on single-cell RNA-seq data
3D Slicer plugin for automatic segmentation and generation of standardized clinical reports for the most common brain tumors, using MRI volumes
Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-parametric MRI based Convolutional Neural Network Model
Clinical oncology tumor board decision support system made by the Decider project.
tumor - cancer cell line alignment. Use it on the depmap portal or install it with pip.
This repository covers a brain scan tumor classification project for the University of Washington DATA 515 course. In our project we train a CNN to predict if a MRI scan (.jpg, .png, .jpeg) is tumorous or not.
:whale: Dockerized WES pipeline for variants identification in mathced tumor-normal samples
A clinical genomics-guided prioritizing strategy enables accurately selecting proper cancer cell lines for biomedical research
The work presented explains how to segment the brain tumour area in absence of interaction with user basing his technique on a saliency map constructed from three different resonance techniques.
GATK 4 Mutect2 Somático
Repository with models, experiments and approaches for the BraTS 2017 and iSeg segmentation challenges.
predict whether the tumor is Malignant or Benign.
A Brain Tumor Classification and Segmentation tool to easily detect from Magnetic Resonance Images or MRI. It works on a Convolutional Neural Network created using Keras.
"Derin Öğrenme Teknolojisi ile Beyin Tümörü Tespiti ve Segmentasyonu" konusu ele alınmış olup, tümörü kolaylıkla ve yüksek doğrulukta tespit edebilen bir bilgisayar destekli tümör tespit sistemi geliştirilmiştir.
Predicting & Classifying Brain tumor using CNN model
Weighted In Silico Pathology: a novel approach to assess intra-tumoral heterogeneity
Comparison of Tumor and Normal Cells Protein-Protein Interaction Network Parameters
image processing exercises with google colab
:hugs: neukit: web application for automatic brain extraction and preoperative tumor segmentation from MRI
Warlock is a snakemake workflow to spawn multiple demons (deme-based oncology models) as jobs running around on a cluster environment 😈😈
Building a detection model using a convolutional neural network in Keras.
Tumor Computer Vision Project - PyResearch