activity
19982024
most citedMulticlass Wound Image Classification using an Ensemble Deep CNN-based Classifier

113 citations · 319 across the 12 of their papers we have counts for

collaborators

12 papers

eess.IV2024★ 2 cited

Wound Tissue Segmentation in Diabetic Foot Ulcer Images Using Deep Learning: A Pilot Study

Mrinal Kanti Dhar, Chuanbo Wang, Yash Patel +5

Identifying individual tissues, so-called tissue segmentation, in diabetic foot ulcer (DFU) images is a challenging task and little work has been published, largely due to the limi…

cs.CV2023★ 2 cited

Integrated Image and Location Analysis for Wound Classification: A Deep Learning Approach

Yash Patel, Tirth Shah, Mrinal Kanti Dhar +4

The global burden of acute and chronic wounds presents a compelling case for enhancing wound classification methods, a vital step in diagnosing and determining optimal treatments.…

eess.IV2022★ 3 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.IV2022★ 8 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.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.AI2021★ 22 cited

Synthesizing time-series wound prognosis factors from electronic medical records using generative adversarial networks

Farnaz H. Foomani, D. M. Anisuzzaman, Jeffrey Niezgoda +4

Wound prognostic models not only provide an estimate of wound healing time to motivate patients to follow up their treatments but also can help clinicians to decide whether to use…

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…

cs.CV2020★ 41 cited

A Mobile App for Wound Localization using Deep Learning

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

We present an automated wound localizer from 2D wound and ulcer images by using deep neural network, as the first step towards building an automated and complete wound diagnostic s…

astro-ph1998★ 33 cited

Gigahertz Peaked Spectrum sources from the Jodrell Bank-VLA Astrometric Survey

A. Marecki, H. Falcke, J. Niezgoda +2

Observations with MERLIN at 408 MHz have been used to establish the low-frequency part of the spectra of more than a hundred compact radio sources taken from the part of the Jodrel…