saruarlive Goto Github PK

1p19q_codeletionradiogenomics22

approaching-any-machine-learning-problems

Contains the note for the Approaching(Almost) any Machine Learning Problem by Abhishek Thakur.

brats2018-tumor-segmentation

We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. We also integrate location information with DeepMedic and 3D UNet by adding additional brain parcellation with original MR images.

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

glioma-grading23

Glioma segmentation and grade prediction using multiparametric 3D MRI and deep learning approaches

glioma-localization23

If brain glioblastomas integrate with local neuronal function, it is important to know where they grow – a case-based investigation

glioma-segmentation23

Brain tumor segmentation from multiparametric MRI using a multi-encoder U-Net architecture

idhradiogenomics2022

image2text

Converting image to text using Tesseract optical character recognition engine

istn

Image-and-Spatial Transformer Networks

medicalimageclassification_fastai2_2d

medicalnet

Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

medicalzoopytorch

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

niftidataset

pytorch dataset class for reading and transforming NIfTI files

polyp-segproject

Polyp segmentation using fastai_v2

ranger21

Ranger deep learning optimizer rewrite to use newest components

rapidsaispeedtest

simpleitk-notebooks

Jupyter notebooks for learning how to use SimpleITK

skullstripping

Skull stripping of large and heterogenous MRI images

stat453-deep-learning-ss20

STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)

tutorials

MONAI tutorials.