zach jerzy's repositories
Medical_Imaging
CNNs and ML regression methods for 3D brain MRI segmentation and patient age regression
Multiclass-Classification-on-STL-10-dataset-using-FineTuned-Resnet50-and-SVM-Classifier
a) Features extracted from the last fully-connected layer of pretrained Rsenet50 on ImageNet dataset is used to train a multiclass SVM classifier on STL-10 dataset
3DCNN-MRI
Cerebral Microbleeds (CMB) diagnostic of 3D SWI-MRI using Spatial Pyramid Pooling modified 3D CNNs
Automated-Electronic-Health-Record-Based-detection-of-ARDS
Automated Electronic Health Record Based detection of ARDS
AutoRadiomics
The easiest tool for experimenting with radiomics features.
Brain-Tumor-VSegmentation-Using-3D-CNN
In this work, two neural networks architectures based on the Unet network have been designed and trained to automatically segment different tumor substructures using the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2020 training dataset
ChatGLM2-6B
ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
Cobb_Angle_calculator
Automatic cobb angle detection using the YOLO neural network.
DeepHistology
A pan-cancer platform for mutation prediction from routine histology
EssayKiller_V2
基于开源GPT2.0的初代创作型人工智能 | 可扩展、可进化
FAST
Fusion models for Atomic and molecular STructures (FAST)
idears_ukb
auto-ml UKB app
IDHpredict
Multiple cases testing script - from DICOM files to IDH prediction score. This is entirely based on yoonchoi-neuro/automated_hybrid_IDH repo that predicts IDH mutation status from MRI glioma images using a machine learning hybrid model.
LiTS---Liver-Tumor-Segmentation-Challenge
LiTS - Liver Tumor Segmentation Challenge
MedMNIST
[pip install medmnist] 18 MNIST-like Datasets for 2D and 3D Biomedical Image Classification
Multiple-Pooling-in-Convolutional-Neural-Networks-Max-Range-Pooling-
Model Architecture consist of a convolution layer followed by a Max Pooling layer. The convolution layer is used to create minimum pooling layer, which in turn is subtracted from a max pool layer to obtain a range pooling layer. The max pooling layer and range pooling layers are concatenated to get the final pooling layer.
perfu-net
Code for PerfU-Net.
playground
A central hub for gathering and showcasing amazing projects that extend OpenMMLab with SAM and other exciting features.
pretorched-x
Pretrained Image & Video ConvNets and GANs for PyTorch: NASNet, ResNeXt (2D + 3D), ResNet (2D + 3D), InceptionV4, InceptionResnetV2, Xception, DPN, NonLocalNets, R(2+1)D nets, MultiView CNNs, Temporal Relation Networks, BigGANs StyleGANs, etc.
pytorch-image-models
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
QMITH
MRI-based quantitative measure of intra-tumoral heterogeneity in breast cancer
RadImageNet
RadImageNet, a pre-trained convolutional neural networks trained solely from medical imaging to be used as the basis of transfer learning for medical imaging applications.
Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".