194 citations · 356 across the 9 of their papers we have counts for
9 papers
A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal FDG PET imaging
Christian Salomonsen, Luigi T Luppino, Fredrik Aspheim +7
Dynamic positron emission tomography (PET) and kinetic modeling are pivotal in advancing tracer development research in small animal studies. Accurate kinetic modeling requires pre…
Filling of incomplete sinograms from sparse PET detector configurations using a residual U-Net
Klara Leffler, Luigi Tommaso Luppino, Samuel Kuttner +2
Long axial field-of-view PET scanners offer increased field-of-view and sensitivity compared to traditional PET scanners. However, a significant cost is associated with the densely…
Postoperative glioblastoma segmentation: Development of a fully automated pipeline using deep convolutional neural networks and comparison with currently available models
Santiago Cepeda, Roberto Romero, Daniel Garcia-Perez +11
Accurately assessing tumor removal is paramount in the management of glioblastoma. We developed a pipeline using MRI scans and neural networks to segment tumor subregions and the s…
Towards Targeted Change Detection with Heterogeneous Remote Sensing Images for Forest Mortality Mapping
Jørgen A. Agersborg, Luigi T. Luppino, Stian Normann Anfinsen +1
Several generic methods have recently been developed for change detection in heterogeneous remote sensing data, such as images from synthetic aperture radar (SAR) and multispectral…
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
Luigi T. Luppino, Mads A. Hansen, Michael Kampffmeyer +4
Image translation with convolutional autoencoders has recently been used as an approach to multimodal change detection in bitemporal satellite images. A main challenge is the align…
Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi +4
Image translation with convolutional neural networks has recently been used as an approach to multimodal change detection. Existing approaches train the networks by exploiting supe…
Unsupervised Image Regression for Heterogeneous Change Detection
Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser +1
Change detection in heterogeneous multitemporal satellite images is an emerging and challenging topic in remote sensing. In particular, one of the main challenges is to tackle the…
Remote sensing image regression for heterogeneous change detection
Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser +1
Change detection in heterogeneous multitemporal satellite images is an emerging topic in remote sensing. In this paper we propose a framework, based on image regression, to perform…
A clustering approach to heterogeneous change detection
Luigi Tommaso Luppino, Stian Normann Anfinsen, Gabriele Moser +4
Change detection in heterogeneous multitemporal satellite images is a challenging and still not much studied topic in remote sensing and earth observation. This paper focuses on co…