113 citations · 631 across the 32 of their papers we have counts for
7 papers · 1 filter
A Deep Learning Study on Osteosarcoma Detection from Histological Images
D M Anisuzzaman, Hosein Barzekar, Ling Tong +2
In the U.S, 5-10\% of new pediatric cases of cancer are primary bone tumors. The most common type of primary malignant bone tumor is osteosarcoma. The intention of the present work…
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…
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…
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…
Fully Automatic Intervertebral Disc Segmentation Using Multimodal 3D U-Net
Chuanbo Wang, Ye Guo, Wei Chen +1
Intervertebral discs (IVDs), as small joints lying between adjacent vertebrae, have played an important role in pressure buffering and tissue protection. The fully-automatic locali…
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…
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…