activity
20102022
most citedFast Mojette Transform for Discrete Tomography

6 citations · 9 across the 5 of their papers we have counts for

collaborators

9 papers

eess.IV20241 cited

Machine Learning Applications in Traumatic Brain Injury: A Spotlight on Mild TBI

Hanem Ellethy, Shekhar S. Chandra, Viktor Vegh

Traumatic Brain Injury (TBI) poses a significant global public health challenge, contributing to high morbidity and mortality rates and placing a substantial economic burden on hea…

cs.CV2023

Ugly Ducklings or Swans: A Tiered Quadruplet Network with Patient-Specific Mining for Improved Skin Lesion Classification

Nathasha Naranpanawa, H. Peter Soyer, Adam Mothershaw +4

An ugly duckling is an obviously different skin lesion from surrounding lesions of an individual, and the ugly duckling sign is a criterion used to aid in the diagnosis of cutaneou…

eess.IV20231 cited

Application of Machine Learning in Melanoma Detection and the Identification of 'Ugly Duckling' and Suspicious Naevi: A Review

Fatima Al Zegair, Nathasha Naranpanawa, Brigid Betz-Stablein +3

Skin lesions known as naevi exhibit diverse characteristics such as size, shape, and colouration. The concept of an "Ugly Duckling Naevus" comes into play when monitoring for melan…

cs.CV2023

TriFormer: A Multi-modal Transformer Framework For Mild Cognitive Impairment Conversion Prediction

Linfeng Liu, Junyan Lyu, Siyu Liu +3

The prediction of mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD) is important for early treatment to prevent or slow the progression of AD. To accurately pr…

cs.CV20231 cited

Evidence-aware multi-modal data fusion and its application to total knee replacement prediction

Xinwen Liu, Jing Wang, S. Kevin Zhou +2

Deep neural networks have been widely studied for predicting a medical condition, such as total knee replacement (TKR). It has shown that data of different modalities, such as imag…

eess.IV20232 cited

Explainable Semantic Medical Image Segmentation with Style

Wei Dai, Siyu Liu, Craig B. Engstrom +1

Semantic medical image segmentation using deep learning has recently achieved high accuracy, making it appealing to clinical problems such as radiation therapy. However, the lack o…