The veins of the nucleus dentatus: Anatomical and radiological findings. - Antonio Di Ieva; Manfred Tschabitscher; Renato Juan Galzio; Günther Grabner; Claudia Kronnerwetter; Georg Widhalm; Christian Matula; Siegfried Trattnig (NeuroImage, 2011)

Detrended fluctuation analysis of brain hemisphere magnetic resonnance images to detect cerebral arteriovenous malformations. - Salim Lahmiri; Mounir Boukadoum; Antonio Di Ieva (ISCAS, 2014)

Fractal-based arteriovenous malformations detection in brain magnetic resonance images. - Salim Lahmiri; Mounir Boukadoum; Antonio Di Ieva (NEWCAS, 2014)

Box-Counting Method in Quantitative Analysis of Images of the Brain. - Nebojsa T. Milosevic; Antonio Di Ieva; Herbert F. Jelinek; Nemanja Rajkovic (CSCS, 2017)

Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction. - Carlo Russo; Sidong Liu; Antonio Di Ieva (BrainLes@MICCAI (1), 2020)

Deep learning for automated cerebral aneurysm detection on computed tomography images. - Xilei Dai; Lixiang Huang; Yi Qian 002; Shuang Xia; Winston Chong; Junjie Liu; Antonio Di Ieva; Xiaoxi Hou; Chubin Ou (Int. J. Comput. Assist. Radiol. Surg., 2020)

Two-stage U-Net++ for Medical Image Segmentation. - Abdulla Al Suman; Shubham Sarda; Md. Asikuzzaman; Alexandra Louise Webb; Diana M. Perriman; Murat Tahtali; Antonio Di Ieva; Mark R. Pickering (DICTA, 2021)

Texture Enhanced Generative Adversarial Network For Stain Normalisation In Histopathology Images. - Cong Cong; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Shlomo Berkovsky; Yang Song 001 (ISBI, 2021)

Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images. - Cong Cong; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Shlomo Berkovsky; Yang Song 001 (MICCAI (8), 2021)

Integrating eye gaze into machine learning using fractal curves. - Robert Ahadizad Newport; Sidong Liu; Antonio Di Ieva (Gaze Meets ML, 2022)

Adaptive Unified Contrastive Learning for Imbalanced Classification. - Cong Cong; Yixing Yang; Sidong Liu; Maurice Pagnucco; Antonio Di Ieva; Shlomo Berkovsky; Yang Song 001 (MLMI@MICCAI, 2022)

Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI. - Carlo Russo; Sidong Liu; Antonio Di Ieva (Medical Biol. Eng. Comput., 2022)

Colour adaptive generative networks for stain normalisation of histopathology images. - Cong Cong; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Shlomo Berkovsky; Yang Song 001 (Medical Image Anal., 2022)

SoftMatch: Comparing Scanpaths Using Combinatorial Spatio-Temporal Sequences with Fractal Curves. - Robert Ahadizad Newport; Carlo Russo; Sidong Liu; Abdulla Al Suman; Antonio Di Ieva (Sensors, 2022)

Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification. - Soham Rohit Chitnis; Sidong Liu; Tirtharaj Dash; Tanmay Tulsidas Verlekar; Antonio Di Ieva; Shlomo Berkovsky; Lovekesh Vig; Ashwin Srinivasan 001 (EMBC, 2023)

A Deep Learning Framework for Skull Stripping in Brain MRI. - Mehnaz Tabassum; Abdulla Al Suman; Carlo Russo; Antonio Di Ieva; Sidong Liu (EMBC, 2023)

Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification. - Litao Yang; Deval Mehta; Sidong Liu; Dwarikanath Mahapatra; Antonio Di Ieva; Zongyuan Ge (MIDL, 2023)

Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification. - Soham Rohit Chitnis; Sidong Liu; Tirtharaj Dash; Tanmay Tulsidas Verlekar; Antonio Di Ieva; Shlomo Berkovsky; Lovekesh Vig; Ashwin Srinivasan 001 (CoRR, 2023)

TPMIL: Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification. - Litao Yang; Deval Mehta; Sidong Liu; Dwarikanath Mahapatra; Antonio Di Ieva; Zongyuan Ge (CoRR, 2023)

Towards Machine Learning-based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection. - David G. Black; Declan Byrne; Anna Walke; Sidong Liu; Antonio Di Ieva; Sadahiro Kaneko; Walter Stummer; Septimiu E. Salcudean; Eric Suero Molina (CoRR, 2023)

AI in Neuro-Oncology: Predicting EGFR Amplification in Glioblastoma from Whole Slide Images Using Weakly Supervised Deep Learning. - Homay Danaei Mehr; Imran Noorani; Priyanka Rana; Antonio Di Ieva; Sidong Liu (AIME (2), 2024)

Cross-Modality Synthesis of T1c MRI from Non-contrast Images Using GANs: Implications for Brain Tumor Research. - Mehnaz Tabassum; Priyanka Rana; Eric Suero Molina; Antonio Di Ieva; Sidong Liu (AIME (2), 2024)

Meta-Transfer Learning for Few-Shot Meningioma Segmentation. - Shenghui Yan; Sidong Liu; Antonio Di Ieva; Maurice Pagnucco; Yang Song 001 (ISBI, 2024)

Deep Learning-Based Correction and Unmixing of Hyperspectral Images for Brain Tumor Surgery. - David G. Black; Jaidev Gill; Andrew Xie; Benoit Liquet; Antonio Di Ieva; Walter Stummer; Eric Suero Molina (CoRR, 2024)

When Eye-Tracking Meets Machine Learning: A Systematic Review on Applications in Medical Image Analysis. - Sahar Moradizeyveh; Mehnaz Tabassum; Sidong Liu; Robert Ahadizad Newport; Amin Beheshti; Antonio Di Ieva (CoRR, 2024)

Diagnostic Performance of Deep Learning for Predicting Gliomas' IDH and 1p/19q Status in MRI: A Systematic Review and Meta-Analysis. - Somayeh Farahani; Marjaneh Hejazi; Mehnaz Tabassum; Antonio Di Ieva; Neda Mahdavifar; Sidong Liu (CoRR, 2024)

Adaptive unified contrastive learning with graph-based feature aggregator for imbalanced medical image classification. - Cong Cong; Sidong Liu; Priyanka Rana; Maurice Pagnucco; Antonio Di Ieva; Shlomo Berkovsky; Yang Song 001 (Expert Syst. Appl., 2024)

Adaptive Clustering for EGFR Amplification Prediction in Glioblastoma: A Variational Autoencoder-Dirichlet Bayesian Gaussian Approach. - Homay Danaei Mehr; Cong Cong; Imran Noorani; Antonio Di Ieva; Sidong Liu (AIME (1), 2025)

Multi-Sequence MRI to Multi-Tracer Pet Generation via Diffusion Model. - Wenjin Zhong; Cong Cong; Ghasem Azemi; Mehnaz Tabassum; Antonio Di Ieva; Sidong Liu (ISBI, 2025)

Towards a Multimodal MRI-Based Foundation Model for Multi-Level Feature Exploration in Segmentation, Molecular Subtyping, and Grading of Glioma. - Somayeh Farahani; Marjaneh Hejazi; Antonio Di Ieva; Emad Fatemizadeh; Sidong Liu (CoRR, 2025)

FoundBioNet: A Foundation-Based Model for IDH Genotyping of Glioma from Multi-Parametric MRI. - Somayeh Farahani; Marjaneh Hejazi; Antonio Di Ieva; Sidong Liu (CoRR, 2025)