19 citations · 34 across the 6 of their papers we have counts for
9 papers
Graph-Radiomic Learning (GrRAiL) Descriptor to Characterize Imaging Heterogeneity in Confounding Tumor Pathologies
Dheerendranath Battalapalli, Apoorva Safai, Maria Jaramillo +6
A significant challenge in solid tumors is reliably distinguishing confounding pathologies from malignant neoplasms on routine imaging. While radiomics methods seek surrogate marke…
Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm
Hongyi Pan, Gorkem Durak, Elif Keles +27
Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. Intraductal papillary mucinous neoplasms (IPMNs), key cancer precursors,…
Evidential Federated Learning for Skin Lesion Image Classification
Rutger Hendrix, Federica Proietto Salanitri, Concetto Spampinato +2
We introduce FedEvPrompt, a federated learning approach that integrates principles of evidential deep learning, prompt tuning, and knowledge distillation for distributed skin lesio…
A Privacy-Preserving Walk in the Latent Space of Generative Models for Medical Applications
Matteo Pennisi, Federica Proietto Salanitri, Giovanni Bellitto +3
Generative Adversarial Networks (GANs) have demonstrated their ability to generate synthetic samples that match a target distribution. However, from a privacy perspective, using GA…
Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images
Federica Proietto Salanitri, Giovanni Bellitto, Simone Palazzo +9
Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more f…
Hierarchical 3D Feature Learning for Pancreas Segmentation
Federica Proietto Salanitri, Giovanni Bellitto, Ismail Irmakci +3
We propose a novel 3D fully convolutional deep network for automated pancreas segmentation from both MRI and CT scans. More specifically, the proposed model consists of a 3D encode…
Diagnosing Colorectal Polyps in the Wild with Capsule Networks
Rodney LaLonde, Pujan Kandel, Concetto Spampinato +2
Colorectal cancer, largely arising from precursor lesions called polyps, remains one of the leading causes of cancer-related death worldwide. Current clinical standards require the…
INN: Inflated Neural Networks for IPMN Diagnosis
Rodney LaLonde, Irene Tanner, Katerina Nikiforaki +5
Intraductal papillary mucinous neoplasm (IPMN) is a precursor to pancreatic ductal adenocarcinoma. While over half of patients are diagnosed with pancreatic cancer at a distant sta…
Deep Multi-Modal Classification of Intraductal Papillary Mucinous Neoplasms (IPMN) with Canonical Correlation Analysis
Sarfaraz Hussein, Pujan Kandel, Juan E. Corral +3
Pancreatic cancer has the poorest prognosis among all cancer types. Intraductal Papillary Mucinous Neoplasms (IPMNs) are radiographically identifiable precursors to pancreatic canc…