Aldo Marzullo

Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy

Purpose: Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma (UTUC). During ureteroscopy, the automatic...

A Logic-Based Framework Leveraging Neural Networks for Studying the Evolution of Neurological Disorders

Deductive formalisms have been strongly developed in recent years; among them, Answer Set Programming (ASP) gained some momentum, and has been lately fruitfully employed in many real-world...

A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture

Ureteroscopy is becoming the first surgical treatment option for the majority of urinary affections. This procedure is performed using an endoscope which provides the surgeon with the visual...

A transfer-learning approach for lesion detection in endoscopic images from the urinary tract

Ureteroscopy and cystoscopy are the gold standard methods to identify and treat tumors along the urinary tract. It has been reported that during a normal procedure a rate of 10-20 % of the lesions...

Biomedical Data Augmentation Using Generative Adversarial Neural Networks

An Unet Boosting Training Strategy for the BraTS-ISBI 2024 Goat Challenge

Mixing Logic Programming and Neural Networks to Support Neurological Disorders Analysis

Graph based neural networks for automatic classification of multiple sclerosis clinical courses

Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet?

A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture

Tensor Factorization of Brain Structural Graph for Unsupervised Classification in Multiple Sclerosis

Classification and Survival Prediction in Diffuse Large B-Cell Lymphoma by Gene Expression Profiling

BioHIPI: Biomedical Hadoop Image Processing Interface

Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks

A Unity-based Da Vinci Robot Simulator for Surgical Training

A tensor-based mutation operator for Neuroevolution of Augmenting Topologies (NEAT)

Assessing Subgroup Fairness in Clinical Missing Data Imputation: A Case Study Using MIMIC-IV

Assessing Utility-Leakage Trade-offs in Coreset Selection for Chest X-Ray Embeddings