TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture.

Overview

TumorInsight

Overview

What is TumorInsight?

TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture. It aims to detect and classify the brain tumours from MRI scans. The detection is done using Image Processing algorithms and classification using Deep learning techniques.
The model is also deployed as a web application using Flask framework.

Download trained model from here.

Features

  • TumorInsight Web App - Technology at your fingertips!
  • Image Segmentation (K-means clustering)
  • Image Processing (Median filtering, morphological processing etc.)
  • RESNET50 architecture for classification
  • Flask framwework for integrating with frontend of web app
  • And More...

Contents

Project Details

TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture. It aims to detect and classify the brain tumours from MRI scans. The detection is done using Image Processing algorithms and classification using Deep learning techniques.
The model is also deployed as a web application using Flask framework.

In addition, you can also customize the following properties according to the need.

  • Lorem ipsum
  • Lorem ipsum
  • Lorem ipsum

Usage

  1. Lorem Ipsum

Project is designed to be easy to use. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

  1. Lorem Ipsum

Lorem ipsum dolor sit amet, consectetur adipiscing elit.

  1. Lorem Ipsum

Finally, call func(arg) in main()

def func(arg):
    return arg

func(input())

Requirements

  • Xcode 10.2.1
  • Swift 5.0

Installation

Follow these steps to use this project.

  1. Clone the repository.
  2. Lorem ipsum

Contribute

Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/NewFeature)
  3. Commit your Changes (git commit -m 'Add some NewFeature')
  4. Push to the Branch (git push origin feature/NewFeature)
  5. Open a Pull Request

Tech Stacks/Tools Used

License

TumorInsight is available under the MIT license. See the LICENSE file for more info.

Author

Pranav Khurana


Owner
Pranav Khurana
Incoming Software Engineer at UBS | Ex-Research Intern at Arizona State University | 2022 Undergrad
Pranav Khurana
UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems

[ICLR 2021] "UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems" by Jiayi Shen, Haotao Wang*, Shupeng Gui*, Jianchao Tan, Zhangyang Wang, and Ji Liu

VITA 39 Dec 03, 2022
根据midi文件演奏“风物之诗琴”的脚本 "Windsong Lyre" auto play

Genshin-lyre-auto-play 简体中文 | English 简介 根据midi文件演奏“风物之诗琴”的脚本。由Python驱动,在此承诺, ⚠️ 项目内绝不含任何能够引起安全问题的代码。 前排提示:所有键盘在动但是原神没反应的都是因为没有管理员权限,双击run.bat或者以管理员模式

御坂17032号 386 Jan 01, 2023
Official implementation of the paper ``Unifying Nonlocal Blocks for Neural Networks'' (ICCV'21)

Spectral Nonlocal Block Overview Official implementation of the paper: Unifying Nonlocal Blocks for Neural Networks (ICCV'21) Spectral View of Nonloca

91 Dec 14, 2022
A python script to lookup Passport Index Dataset

visa-cli A python script to lookup Passport Index Dataset Installation pip install visa-cli Usage usage: visa-cli [-h] [-d DESTINATION_COUNTRY] [-f]

rand-net 16 Oct 18, 2022
Python interface for SmartRF Sniffer 2 Firmware

#TI SmartRF Packet Sniffer 2 Python Interface TI Makes available a nice packet sniffer firmware, which interfaces to Wireshark. You can see this proje

Colin O'Flynn 3 May 18, 2021
Distinguishing Commercial from Editorial Content in News

Distinguishing Commercial from Editorial Content in News In this repository you can find the following: An anonymized version of the data used for my

Timo Kats 3 Sep 26, 2022
GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors

GPU implementation of kNN and SNN GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors Supported by numba cuda and faiss library E

Hyeon Jeon 7 Nov 23, 2022
PyTorch Code for "Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning"

Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning [Project Page] [Paper] Wenlong Huang1, Igor Mordatch2, Pieter Abbeel1,

Wenlong Huang 40 Nov 22, 2022
Pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"

MOSNet pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion" https://arxiv.org/abs/1904.08352 Dependency L

9 Nov 18, 2022
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

Kyle Hundman 844 Dec 28, 2022
Rohit Ingole 2 Mar 24, 2022
Python implementation of MULTIseq barcode alignment using fuzzy string matching and GMM barcode assignment

Python implementation of MULTIseq barcode alignment using fuzzy string matching and GMM barcode assignment.

MT Schmitz 2 Feb 11, 2022
Deeper DCGAN with AE stabilization

AEGeAN Deeper DCGAN with AE stabilization Parallel training of generative adversarial network as an autoencoder with dedicated losses for each stage.

Tyler Kvochick 36 Feb 17, 2022
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

8 Nov 14, 2022
Python Multi-Agent Reinforcement Learning framework

- Please pay attention to the version of SC2 you are using for your experiments. - Performance is *not* always comparable between versions. - The re

whirl 1.3k Jan 05, 2023
TensorFlow implementation for Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How

Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce

Shen Lab at Texas A&M University 8 Sep 02, 2022
DeepGNN is a framework for training machine learning models on large scale graph data.

DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in

Microsoft 45 Jan 01, 2023
Implementation of Memory-Compressed Attention, from the paper "Generating Wikipedia By Summarizing Long Sequences"

Memory Compressed Attention Implementation of the Self-Attention layer of the proposed Memory-Compressed Attention, in Pytorch. This repository offers

Phil Wang 47 Dec 23, 2022
SAPIEN Manipulation Skill Benchmark

ManiSkill Benchmark SAPIEN Manipulation Skill Benchmark (abbreviated as ManiSkill, pronounced as "Many Skill") is a large-scale learning-from-demonstr

Hao Su's Lab, UCSD 107 Jan 08, 2023
Official repository for "Restormer: Efficient Transformer for High-Resolution Image Restoration". SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

Syed Waqas Zamir 906 Dec 30, 2022