Pinned Repositories
365-Days-Computer-Vision-Learning-Linkedin-Post
365 Days Computer Vision Learning Linkedin Post
ANN-PSO
Training Neural Network with Particle Swarm Optimization
BenchENAS
BenchENAS is a platform to help researchers conduct fair comparisons upon Evolutionary algorithm based Neural Architecture Search (ENAS) algorithms.
Classification-Pipeline
This repository contains a pipeline for training classification models using pre trained model in keras. Readme will be updated with step by step process to use this pipeline.
CT_lung_segmentation
Lung segmentation from CT images
kaggle_dsb
Canidadate for the Kaggle 2017 Data Science Bowl - Automatic detection of lung cancer from CT scans
Luna16-1
LUNA(LUng Nodule Analysis) 2016 Segmentation Pipeline
LungTumorSegmentation
unet
unet for image segmentation
ssraghuvanshi's Repositories
ssraghuvanshi/Deep-Chest-Multi-Classification-Deep-Learning-Model-for-Diagnosing-COVID-19-Pneumonia-and-Lung-Canc
ssraghuvanshi/DeepSEED-3D-ConvNets-for-Pulmonary-Nodule-Detection
DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder ConvNets for Pulmonary Nodule Detection
ssraghuvanshi/LIDC-IDRI-Preprocessing
This is the preprocessing step of the LIDC-IDRI dataset
ssraghuvanshi/UNetPlusPlus
Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018
ssraghuvanshi/CA-Net
Code for Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation.
ssraghuvanshi/CHS-Net-COVID-19-hierarchical-segmentation-network
ssraghuvanshi/cnn-classifier
A simple guide to a vanilla CNN for classification and transfer learning
ssraghuvanshi/CNN-COVID-19-classification-using-chest-CT-scan
COVID-19 classification based on chest CT scan using convolutional neural network
ssraghuvanshi/COVID-CT
COVID-CT-Dataset: A CT Scan Dataset about COVID-19
ssraghuvanshi/COVID19-DL
ssraghuvanshi/COVID19_imaging_AI_paper_list
COVID-19 imaging-based AI paper collection
ssraghuvanshi/DeepPATH
Classification of Lung cancer slide images using deep-learning
ssraghuvanshi/FAnTom
Find Anomalies in Tomography. Medical images markup system
ssraghuvanshi/FastFCN
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation.
ssraghuvanshi/goptim
This code could be used for hyperparameter tuning of CNN in objective no. 4 of PhD research work.
ssraghuvanshi/Hands-On-Neural-Networks
Published by Packt
ssraghuvanshi/lidc-binary-classification
This repository contains code to pre-process the LIDC-IDRI dataset of CT-scans with pulmonary nodules into a binary classification problem, easy to use for learning deep learning
ssraghuvanshi/lidc2dicom
Scripts for converting TCIA LIDC-IDRI collection derived data into standard DICOM representation from project-specific XML format.
ssraghuvanshi/lil_nlp_with_tensorflow
ssraghuvanshi/Lung-Cancer-Detection-using-CNN
Lung Cancer Detection using CNN
ssraghuvanshi/Lung-Cancer-Prediction
CNN model to predict lung cancer based on CT scan images
ssraghuvanshi/Medical-Image-Registration-and-Pre-Processing
Register images to MNI152 Template and perform pre-processing
ssraghuvanshi/mit-deep-learning
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
ssraghuvanshi/NAS-Lung
3D NAS for Pulmonary Nodules Classification, PR 2021
ssraghuvanshi/Pneumonia-Detection-using-Deep-Learning
Deep-Pneumonia Framework Using Deep Learning Models based on Chest X-ray Images
ssraghuvanshi/ProjectAiAi
AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charitable hospitals, and organizations like WHO 🌏 We will also release our pretrained models and weights as Medical Imagenet.
ssraghuvanshi/scancovia
ssraghuvanshi/tf-end-to-end-image-classification
TensorFlow End-to-End Image Classification Tutorial using Deep Learning
ssraghuvanshi/U-Det
U-Det: A Modified U-Net architecture with bidirectional feature network for lung nodule segmentation
ssraghuvanshi/Unsuprevised_Seg_via_CNN
An unsupervised (or self-supervised) loss function for binary image segmentation.