Selected Publications
International Conferences:
AnyMap: Learning a General Camera Model for Structure-from-Motion with Unknown Distortion in Dynamic Scenes
A. Porfiri Dal Cin, G. Dikov, J. Ju and M. Ghafoorian
CVPR 2025.
FastCAD: Real-Time CAD Retrieval and Alignment from Scans and Videos Paper
F. Langer, J. Ju, G. Dikov, G. Reitmayr, and M. Ghafoorian
ECCV 2024.
InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning Paper
B. Ehteshami, G. Kumar, A. Royer, C. Louizos, T. Blankevoort, and M. Ghafoorian
BMVC 2024.
3D Distillation: Improving Self-Supervised Monocular Depth Estimation on Reflective Surfaces Paper
X. Shi, G. Dikov, G. Reitmayr, T Kim, and M. Ghafoorian
ICCV 2023.
DG-Recon: Depth-Guided Neural 3D Scene Reconstruction Paper
J. Ju, Ching W. Tseng, O. Bailo, G. Dikov, and M. Ghafoorian
ICCV 2023.
Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs Paper Poster
Video Presentation
O. Ulger, J. Wiederer M. Ghafoorian, V. Belagiannis, and P. Mettes
BMVC 2022.
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation Paper Presentation
E. Stammes, T. Runia, M. Hofmann, and M. Ghafoorian
ICDIP 2021. Best Paper Award.
Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation
Paper
Video Presentation
M. Bakhtiariziabari and M. Ghafoorian
MCICCAI '20 Machine Learning for Medical Imaging.
I Bet You Are Wrong: Gambling Adversarial Networks for Structured Semantic Segmentation Paper Poster
L. Samson, N. van Noord, O. Booij, M. Hofmann E. Gavves and M. Ghafoorian
ICCV '19 Computer Vision for Road Scene Understanding and Autonomous Driving.
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection Paper Poster
M. Ghafoorian, C. Nugteren, N. Baka, O. Booij, M. Hofmann
ECCV '18 Computer Vision for Road Scene Understanding and Autonomous Driving.
Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR Paper
M. Ghafoorian*, J. Teuwen*, R. Manniesing, F-E de Leeuw, B. van Ginneken, N. Karssemeijer, B. Platel
in proceedings of SPIE Medical Imaging, 2018.
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation Paper Poster
M. Ghafoorian*, A. Mehrtash*, T. Kapur, N. Karssemeijer, E. Marchiori, M. Pesteie, C. Guttmann, F-E de Leeuw, C. Tempany, B. van Ginneken, A. Fedorov, P, Abolmaesumi, B. Platel, W. Wells III,
Medical Image Computing and Computer Assisted Interventions (MICCAI) 2017.
Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation Paper
Presentation
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, F.E. de Leeuw, B. van Ginneken and B. Platel,
in IEEE International Symposium on Biomedical Imaging, 2016
Classification of Clinical Significance of MRI Prostate Findings Using 3D Convolutional Neural Networks Paper
A. Mehrtash, A. Sedghi, M. Ghafoorian, M. Taghipour, C. Tempany, W. Wells III, T. Kapur, P. Mousavi, P. Abolmaesumib, and A. Fedorov,
in proceedings of SPIE Medical Imaging, 2017
A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation Paper
K. Vijverberg, M. Ghafoorian, I. W.M. van Uden, F.E. de Leeuw, B. Platel and T. Heskes,
in proceedings of SPIE Medical Imaging, 2016
Small white matter lesion detection in cerebral small vessel disease Paper Presentation
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, F.E. de Leeuw, E. Marchiori and B. Platel,
in proceedings of SPIE Medical Imaging, 2015
Computer aided detection of brain micro-bleeds in traumatic brain injury Poster
T. van den Heuvel, M. Ghafoorian, A. van der Eerden, B. Goraj, T. Andriessen, B. ter Haar Romeny and B. Platel,
in proceedings of SPIE Medical Imaging, 2015
Automatic abstraction in reinforcement learning using ant system algorithm Paper Presentation
M. Ghafoorian, N. Taghizadeh and H. Beigy,
in AAAI Spring Symposium: Lifelong Machine Learning, 2013
* represents equal contributions
International Journals:
Location sensitive deep convolutional neural networks for segmentation of white matter hyperintensities Paper
M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, C. Sanchez, G. Litjens, F.E. de Leeuw, B. van Ginneken, E. Marchiori and B. Platel,
Nature Scientific Reports 2017.
Deep Mutli-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin Paper
M. Ghafoorian, N. Karssemeijer, T. Heskes, M. Bergkamp, J. Wissink, J. Obels, K. Keizer, F.E. de Leeuw, B. van Ginneken, E. Marchiori and B. Platel,
NeuroImage Clin. 2017.
Automated Detection of White Matter Hyperintensities of All Sizes in Cerebral Small Vessel Disease
M. Ghafoorian, N. Karssemeijer, I. van Uden, F.E. de Leeuw, T. Heskes, E. Marchiori and B. Platel,
Medical Physics 2016.
A Survey on Deep Learning in Medical Image Analysis Paper
G. Litjens, T. Kooi, B. Ehteshami, A. Setio, F, Ciompi, M. Ghafoorian, J. van der Laak, B. van Ginneken, and C. Sanchez,
Medical Image Analaysis 2017.
Automatic needle segmentation and localization in MRI with 3-D convolutional neural networks: application to MRI-targeted prostate biopsy
A. Mehrtash, M. Ghafoorian, G. Pernelle, A. Ziaei, F. Heslinga, K. Tuncali, A. Fedorov, R. Kikinis, C. Tempany, W. Wells, P. Abolmaesumi, T. Kapur
IEEE Transactions on Medical Imaging 2018.
Theses:
Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers, Doctoral Thesis, 2018. PDF
Automatic Skill Characterization in Reinforcement Learning using Community Detection Approach, Master's Thesis, 2012. PDF (In Farsi)