most citedMulticlass Wound Image Classification using an Ensemble Deep CNN-based Classifier

113 citations · 208 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021★ 76 cited

Multi-modal Wound Classification using Wound Image and Location by Deep Neural Network

D. M. Anisuzzaman, Yash Patel, Behrouz Rostami +3

Wound classification is an essential step of wound diagnosis. An efficient classifier can assist wound specialists in classifying wound types with less financial and time costs and…

cs.CV2021★ 1 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…

cs.CV2020★ 113 cited

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★ 14 cited

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…

cs.CY2020★ 4 cited

Image Based Artificial Intelligence in Wound Assessment: A Systematic Review

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

Efficient and effective assessment of acute and chronic wounds can help wound care teams in clinical practice to greatly improve wound diagnosis, optimize treatment plans, ease the…