Software
Primary software developer named between parentheses
SLiMe
Code supporting our work on SLiMe: Segment-Like-Me paper
(Aliaghar Khaniu)
SyRaC
Code supporting our work on SYRAC: Synthesize, Rank, and Count
(Adriano D’Alessandro)
SubPrecisionContactDetection (MCS-DETECT)
Code supporting our Journal of Cell Biology paper on automatic sub-precision membrane contact site detection, in our paper: Membrane contact site detection (MCS-DETECT) reveals dual control of rough mitochondria-ER contacts
(Ben Cardoen)
Code supporting our 2023 paper: Orthogonal Multi-frequency Fusion Based Image Reconstruction and Diagnosis in Diffuse Optical Tomography.
(Hanene Ben Yedder and Ben Cardoen)
Code supporting our 2022 IEEE TMI paper: Multitask Deep Learning Reconstruction and Localization of Lesions in Limited Angle Diffuse Optical Tomography
(Hanene Ben Yedder and Ben Cardoen)
Code supporting our MICCAI 2019 paper: Limited-angle diffuse optical tomography image reconstruction using deep learning.
(Hanene Ben Yedder and Ben Cardoen)
Code supporting our MICCAI MLMIR 2018 paper: Deep Learning based Image Reconstruction for Diffuse Optical Tomography.
(Hanene Ben Yedder and Aïcha Bentaieb)
Code supporting our MICCAI 2023 paper: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets
(Siyi Du)
Code supporting our paper: DermSynth3D: Synthesis of in-the-wild annotated dermatology images
(Ashish Sinha, Jeremy Kawahara, Arezou Pakzad, Kumar Abhishek)
Code supporting our CRV 2023 paper: Learning-to-Count by Learning-to-Rank
(Adriano D’Alessandro)
Code supporting our paper DataCurator.jl: Efficient, portable, and reproducible validation, curation, and transformation of large heterogeneous datasets using human-readable recipes compiled into machine verifiable templates
(Ben Cardoen)
Reference Julia implementation of colocalization metrics for 2D and 3D (microscopy) images
(BenCardoen)
Code supporting our paper Log-Paradox: Necessary and sufficient conditions for confounding statistically significant pattern reversal under the log-transform
(Ben Cardoen)
Code supporting our two papers: MedIA - Guidelines and evaluation of clinical explainable AI in medical image analysis; and AAAI: Evaluating Explainable AI on a Multi-Modal Medical Imaging Task: Can Existing Algorithms Fulfill Clinical Requirements?
(Weina Jin)
Code supporting our paper: Mouth2audio: Intelligible Audio Synthesis from Videos with Distinctive Vowel Articulation
(Saurabh Garg)
Active Learning from Noisy Teacher
Code supporting our CMIG paper: Active Deep Learning from a Noisy Teacher for Semi-supervised 3D Image Segmentation: Application to COVID-19 Pneumonia Infection in CT
(Arafat Hussain)
Code supporting our NeurIPS paper MaskTune: Mitigating Spurious Correlations by Forcing to Explore
(Saeid Asgari, Aliasghar Khani)
Learning to Segment from Noisy Annotations
Code supporting our MICCAI MIL3ID paper on Learning to Segment Skin Lesions from Noisy Annotations
(Zahra Mirikharaji)
Code supporting our MICCAI 2018 paper on star shape prior for CNN based image segmentation
(Zahra Mirikharaji)
Code supporting our work on SPECHT: Self-tuning Plausibility Based Object Detection Enables Quantification of Conflict in Heterogeneous Multi-scale Microscopy
(Ben Cardoen)
CIRCLe
Code supporting our ECCV ISIC paper CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions
(Arezou Pakzad)
FairDisCo
Code supporting our ECCV ISIC paper, FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning
(Siyi Du)
WhiteNNer
Code supporting our ICCV VRMI paper on WhiteNNer-Blind Image Denoising via Noise Whiteness Priors
(Saeed Izadi)
Code supporting our AAAI paper on Evaluating Explainable AI on Multi-Modal Medical Imaging Task
(Weina Jin)
Code supporting our Medical Image Analysis paper: Skin3D: Detection and Longitudinal Tracking of Pigmented Skin Lesions in 3D Total-Body Textured Meshes
(Mengliu Zhao, Jeremy Kawahara, Kumar Abhishek, and Sajjad Shamanian)
Code supporting our IEEE TMI paper: ERGO: efficient recurrent graph optimized emitter density estimation in single molecule localization microscopy.
(Ben Cardoen)
Learning-to-Augment Noisy & Denoised Data
Code supporting our paper Computers in Biology and Medicine 2021 paper: Learning-to-Augment Strategy using Noisy and Denoised Data: Improving Generalizability of Deep CNN for the Detection of COVID-19 in X-ray Images
(Mohammad Momeny)
Code supporting our papers CMIG2021, MICCAI2019, MICCAI MLMI 2019 for 2D ImHistNet and 3D ImHistNet - Learnable Image Histogram-based DNN.
(Arafat Hussain)
Generalizable Feature Learning with Class Imbalance
Code supporting our MICCAI 2019 paper: Generalizable Feature Learning in the Presence of Data Bias and Domain Class Imbalance: Application to Skin Lesion Classification
(Chris Yoon)
A loss function for training deep segmentation models based on the Matthews Correlation Coefficient (supporting our ISBI 2021 paper)
(Kumar Abhishek)
Super-Resolution NETwork Analysis, SuperResNET, is an integrated software for the analysis of 3D single molecule localization microscopy (SMLM) point cloud data. It consists of computational modules to read, pre-process, post-process, quantify, and visualize 3D SMLM data. SuperResNET allows the user to extract, visualize, and analyze biological clusters. SuperResNET is largely based on the original Scientific Reports 2018 and Scientific Reports 2019 works.
(Ismail Khater)
Scanner Invariant Deep Learning Segmentation
Code for ISBI 2020 paper: Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI (video)
(Shahab Aslani)
Code for CVPR 2019 paper: A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
(Saeid Asgari and Kumar Abhishek)
Code for CMIG 2019 paper: Combo loss: Handling input and output imbalance in multi-organ segmentation
(Saeid Asgari)
Missing MRI Pulse Sequence Synthesis using Multi-Modal Generative Adversarial Network
(Anmol Sharma)
Illumination-based Transformations for Skin Lesion Images
Generating transformations based on illumination information and color imaging of the skin for RGB skin lesion images.
(Kumar Abhishek)
Superresolution visualization of 3D protein localization data from a range of super-resolution microscopes
(Ben Cardoen)
Code for AECNN: Adversarial and Enhanced CNN for data-efficient segmentation of gastrointestinal polyps from colonoscopy images
(Saeed Izadi)
Code for ISBI 2018 paper: Generative adversarial networks to segment skin lesions
(Saeed Izadi)
Super-Resolution via Bilinear Pooling
Code for MICCAI 2019 MLMIR: Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy
(Saeed Izadi)
Super-Resolution (Confocal Laser Endomicroscopy)
Code for MICCAI 2018: Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?
(Saeed Izadi)
Trained CNN to detect four types of dermoscopic criteria based on our winning entry for Part 2 of the 2017 ISIC Skin Challenge
(Jeremy Kawahara)
SMLM PC3 Cav1/CAVIN1 Point Cloud Data
3D point clouds of super resolution molecule localization microscopy (SMLM) of Cav1 protein in prostate cancer (PC3) and CAVIN1/PTRF transfected PC3 (PC3-PTRF) cells
(Ismail Khater)
Melanoma Recognition via Visual Attention
Attention-based method for melanoma recognition, with attention map regularization
(Yiqi Yan and Jeremy Kawahara)
Local Synthetic Instances (LSI)
An oversampling method for synthetic data generation or similar tasks. It is designed for the challenging case of high-dimensional, non-gaussian data with low sample size
(Colin Brown)
Recurrent Visual Attention Model for Analyzing Histopathology Whole Slide Images
(Aïcha Bentaieb)
Highlight vascular structures exhibiting radial distension pulsatile motions
(Alborz Amir-Khalili)
Take a field of diffusion orientation distribution functions (ODF) and map them to a graph representation
(Brian Booth)
Take a diffusion MRI scan and generate a graph representation, combined with Dijkstra’s algorithm to perform minimal path tractography.
(Brian Booth)
MATLAB toolbox to highlight corners, tubular structures, and sheet-like structures in diffusion tensor images.
(Brian Booth & Krishna Nand)
MATLAB code for segmenting cervical cells, based on "A Variational Approach for Overlapping Cell Segmentation"
(Masoud Nosrati)
Image Data Augmentation Tool: Simulate novel images with ground truth segmentations from a single image-segmentation pair
(Brian Booth)
MATLAB viewer for 3D scalar, vector, and tensor-valued medical images
(Hossein Badakhshannoory)
Software library for manipulating multi-region, probabilistic shapes using Aitchison geometry
(Shawn Andrews)
Simulate 3D images of vascular trees based on oxygen demand maps and physical parameters
(Preet Jassi)
Perception-based visualization of manifold-valued medical images using distance preserving dimensionality reduction
(Chris McIntosh)
ITK and ITK Image IO on Apple iOS
Documentation and code for running ITK on iOS devices (iPod touch, iPhone, iPad)
(Boris Shabash & Zhi Feng Huang)
Intuitive and efficient vessel segmentation tool, finds centre-line and boundaries simultaneously
(Miranda Poon and Ryan Dickie)
n-dimensional scale invariant feature transform (SIFT)(3D SIFT, 4D SIFT, etc.)
(Warren Cheung)
Matlab GUI demo for shape representation & (statistics- and operator-based) deformations
See also: Archived software