180 skills found · Page 1 of 6
ChongQingNoSubway / DGR MILCode for paper: DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification [ECCV 2024]
AntonioDeFalco / SCEVANR package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of malignant cells, identifies subclonal structures and analyses the specific and shared alterations of each subpopulation.
LidiaGarrucho / MAMA MIAThe MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations
21Vipin / Medical Image Classification Using Deep LearningTumour is formed in human body by abnormal cell multiplication in the tissue. Early detection of tumors and classifying them to Benign and malignant tumours is important in order to prevent its further growth. MRI (Magnetic Resonance Imaging) is a medical imaging technique used by radiologists to study and analyse medical images. Doing critical analysis manually can create unnecessary delay and also the accuracy for the same will be very less due to human errors. The main objective of this project is to apply machine learning techniques to make systems capable enough to perform such critical analysis faster with higher accuracy and efficiency levels. This research work is been done on te existing architecture of convolution neural network which can identify the tumour from MRI image. The Convolution Neural Network was implemented using Keras and TensorFlow, accelerated by NVIDIA Tesla K40 GPU. Using REMBRANDT as the dataset for implementation, the Classification accuracy accuired for AlexNet and ZFNet are 63.56% and 84.42% respectively.
SartajBhuvaji / Brain Tumor Classification Using Deep Learning AlgorithmsTo Detect and Classify Brain Tumors using CNN and ANN as an asset of Deep Learning and to examine the position of the tumor.
cv-lee / Camelyon17PyTorch implementation for Camelyon17 (Breast Tumor Classification)
masoudnick / Brain Tumor MRI ClassificationBrain Tomur Classification Using Pre-trained Models
LouisFoucard / DSB17 3d Lung Nodule Classifier3d convnet for the classification of nodules/tumor in lung CT scans. Trained on Luna16 for Kaggle's 2017 data science bowl competition (result in top 3%)
SartajBhuvaji / Brain Tumor Classification DataSetThis repository is part of the Brain Tumor Classification Project. The repo contains the unaugmented dataset used for the project
Ahthe / Brain Tumor Prediction MLBrain Tumor Classification Using Deep Learning
fuscc-deep-path / Sc MTOPsc-MTOP is an analysis framework based on deep learning and computational pathology. This framework aims to characterize the tumor ecosystem diversity at the single-cell level. This code provide 1) Hover-Net-based nuclear segmentation and classification; 2) Nuclear morphological and texture feature extraction; 3) Multi-level pairwise nuclear graph construction and spatial topological feature extraction.
yashpasar / Brain Tumor Classification And Detection Machine LearningRefining the Accuracy and Efficiency to classify brain tumor images into malignant and benign using Matlab
infinite-tao / MA MTLNMulti-attention Guided Multi-task Learning Network for Automatic Gastric Tumor Segmentation and Lymph Node Classification
mahdieslaminet / Classification Of Brain Tumors Using MRI ImagesClassification of brain tumors using MRI images based on pretrained models
qqhe-frank / BUS Segmentation And ClassificationMulti-task learning for segmentation and classification of breast tumors from ultrasound images
BoyuLyu / DL Based Tumor ClassificationDeep Learning Based Tumor Type Classification Using Gene Expression Data
farazahmeds / Classification Of Brain Tumor Using Spatiotemporal ModelsClassification of brain tumor in MR images using deep spatiospatial models.
NikonPic / BonetumorNetA Multitask Deep Learning Model for Simultaneous Detection, Segmentation and Classification of Bone Tumors on Radiographs
quqixun / BTClassificationBrain tumor classification on structural MR images of BraTS dataset based on 3D Multi-Scale Convolutional Neural Network, which is a part of my master thesis project.
namanbansalcodes / Brain Tumor Diagnosis Using Deep LearningDeep Learning Model that classifies brain tumor from images
