4 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
What Matters is the Prompt: Prompt Sensitivity and Prompt Generation in Foundation Models for Lung Nodule Segmentation
Jorge F. Lazo, Xixi Liu, Andreas Hallqvist +5
Lung nodule segmentation in computed tomography is essential for extracting clinically relevant information for lung cancer assessment and treatment planning. Foundation models hav…
Semi-supervised Bladder Tissue Classification in Multi-Domain Endoscopic Images
Jorge F. Lazo, Benoit Rosa, Michele Catellani +6
Objective: Accurate visual classification of bladder tissue during Trans-Urethral Resection of Bladder Tumor (TURBT) procedures is essential to improve early cancer diagnosis and t…
A transfer-learning approach for lesion detection in endoscopic images from the urinary tract
Jorge F. Lazo, Sara Moccia, Aldo Marzullo +5
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…
Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy
Jorge F. Lazo, Aldo Marzullo, Sara Moccia +4
Purpose: Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma (UTUC). During ureteroscopy, the a…
A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture
Jorge F. Lazo, Aldo Marzullo, Sara Moccia +4
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…
Comparison of different CNNs for breast tumor classification from ultrasound images
Jorge F. Lazo, Sara Moccia, Emanuele Frontoni +1
Breast cancer is one of the deadliest cancer worldwide. Timely detection could reduce mortality rates. In the clinical routine, classifying benign and malignant tumors from ultraso…