activity
20152022
most citedFUSeg: The Foot Ulcer Segmentation Challenge

8 citations · 18 across the 6 of their papers we have counts for

collaborators

9 papers

eess.IV20223 cited

Wound Severity Classification using Deep Neural Network

D. M. Anisuzzaman, Yash Patel, Jeffrey Niezgoda +2

The classification of wound severity is a critical step in wound diagnosis. An effective classifier can help wound professionals categorize wound conditions more quickly and afford…

eess.IV20228 cited

FUSeg: The Foot Ulcer Segmentation Challenge

Chuanbo Wang, Amirreza Mahbod, Isabella Ellinger +4

Acute and chronic wounds with varying etiologies burden the healthcare systems economically. The advanced wound care market is estimated to reach $22 billion by 2024. Wound care pr…

cs.CV20211 cited

Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks

Behrouz Rostami, Jeffrey Niezgoda, Sandeep Gopalakrishnan +1

Millions of people are affected by acute and chronic wounds yearly across the world. Continuous wound monitoring is important for wound specialists to allow more accurate diagnosis…

eess.IV2020

C-Net: A Reliable Convolutional Neural Network for Biomedical Image Classification

Hosein Barzekar, Zeyun Yu

Cancers are the leading cause of death in many countries. Early diagnosis plays a crucial role in having proper treatment for this debilitating disease. The automated classificatio…

cs.CV2020

Multiclass Wound Image Classification using an Ensemble Deep CNN-based Classifier

Behrouz Rostami, D. M. Anisuzzaman, Chuanbo Wang +3

Acute and chronic wounds are a challenge to healthcare systems around the world and affect many people's lives annually. Wound classification is a key step in wound diagnosis that…

eess.IV2020

Fully Automatic Wound Segmentation with Deep Convolutional Neural Networks

Chuanbo Wang, DM Anisuzzaman, Victor Williamson +5

Acute and chronic wounds have varying etiologies and are an economic burden to healthcare systems around the world. The advanced wound care market is expected to exceed $22 billion…