activity
20192024
most citedManual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI

65 citations · 90 across the 9 of their papers we have counts for

collaborators

9 papers

eess.IV2024

A self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging

Peichao Li, Oscar MacCormac, Jonathan Shapey +1

Hyperspectral imaging holds promises in surgical imaging by offering biological tissue differentiation capabilities with detailed information that is invisible to the naked eye. Fo…

eess.IV2023★ 14 cited

Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: Application to surgical imaging

Peichao Li, Muhammad Asad, Conor Horgan +3

Hyperspectral imaging has the potential to improve intraoperative decision making if tissue characterisation is performed in real-time and with high-resolution. Hyperspectral snaps…

eess.IV2021

Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction

Peichao Li, Michael Ebner, Philip Noonan +5

Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single…

physics.optics2021★ 3 cited

Methodology development and evaluation of optical properties characterisation of small size tissue samples

Yijing Xie, Jonathan Shapey, Eli Nabavi +4

Integrating sphere (IS) techniques combined with an inverse adding doubling (IAD) algorithm have been widely used for determination of optical properties of ex vivo tissues. Semi-i…

eess.IV2020★ 65 cited

Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI

Hari McGrath, Peichao Li, Reuben Dorent +6

Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. Current clinical practice is to measure the diameter of…

eess.IV2019★ 1 cited

Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle

Zhao-Yang Wang, Xiao-Yun Zhou, Peichao Li +2

3D shape instantiation which reconstructs the 3D shape of a target from limited 2D images or projections is an emerging technique for surgical intervention. It improves the current…

eess.IV2019

Z-Net: an Anisotropic 3D DCNN for Medical CT Volume Segmentation

Peichao Li, Xiao-Yun Zhou, Zhao-Yang Wang +1

Accurate volume segmentation from the Computed Tomography (CT) scan is a common prerequisite for pre-operative planning, intra-operative guidance and quantitative assessment of the…

eess.IV2019★ 3 cited

U-Net Training with Instance-Layer Normalization

Xiao-Yun Zhou, Peichao Li, Zhao-Yang Wang +1

Normalization layers are essential in a Deep Convolutional Neural Network (DCNN). Various normalization methods have been proposed. The statistics used to normalize the feature map…

cs.CV2019★ 4 cited

One-stage Shape Instantiation from a Single 2D Image to 3D Point Cloud

Xiao-Yun Zhou, Zhao-Yang Wang, Peichao Li +2

Shape instantiation which predicts the 3D shape of a dynamic target from one or more 2D images is important for real-time intra-operative navigation. Previously, a general shape in…