salusanga

CCL-SC

Official implementation of ICML'24 paper Confidence-aware Contrastive Learning for Selective Classification.

Foundation-Models-for-Medical-Imagery

Training and Tuning Strategies for Foundation Models in Medical Imaging

fd-shifts

A Benchmark for Failure Detection under Distribution Shifts in Image Classification

MedYOLO

A 3D bounding box detection model for medical data.

towards-better-sel-cls

uia_segmentation

nnUNet

MedSAM

Segment Anything in Medical Images

TorchCP

A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

Conformal-Learning

detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

conformal_training

This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classifiers".

ltt

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

adafocal

Code for the paper "AdaFocal: Calibration-aware Adaptive Focal Loss"

conformal_classification

Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

calibration-object-detection

Codebase for "Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection", published at WACV 2024.

pareto-testing

Code for "Efficiently Controlling Multiple Risks with Pareto Testing"

MONAI

AI Toolkit for Healthcare Imaging

research_project_metastasis

metastasis_CVL

3D detection and segmentation of brain metastases with 3D Mask R-CNN.

conformal_railway_signal_detection

Confident Object Detection via Conformal Prediction and Conformal Risk Control: an Application to Railway Signaling

conformal-risk

Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vision and natural language processing.

TriadNet

Repository for the paper "TriadNet: Sampling-free predictive intervals for lesional volume in 3D brain MR images"

nnDetection

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.

medicaldetectiontoolkit

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

MedMNIST

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

AVUC

Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

focal_calibration

Code for the paper "Calibrating Deep Neural Networks using Focal Loss"

adamatch

NN_calibration

Calibration of Convolutional Neural Networks