DETECTION OF REPLICATION FORKS IN EM IMAGES USING FASTER R-CNN

被引：0
|
作者：
Zhao, Wei [1 ]
Manolika, Eleni Maria [1 ]
Chaudhuri, Arnab Ray [1 ]
Smal, Ihor [1 ,2 ]
机构：
[1] Erasmus MC, Dept Mol Genet, POB 2040, NL-3000 CA Rotterdam, Netherlands
[2] Erasmus MC, Dept Cell Biol, POB 2040, NL-3000 CA Rotterdam, Netherlands
来源：
2021 IEEE 18TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI) | 2021年
关键词：
object detection; deep learning; DNA replication analysis; electron microscopy imaging; CONVOLUTIONAL NETWORKS;
D O I：
10.1109/ISBI48211.2021.9434123
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Currently, one of the most effective techniques to study the mechanisms of DNA replication is using the electron microscopy. Typical imaging experiments result in terabytes of image data, where finding and classifying the replication forks is done manually by experts and is extremely time consuming. Here, we present a fully automated deep learning based approach for detection and classification of DNA replication forks. It is based on the Faster R-CNN architecture, following with additional classification layers. The experimental results using real data indicate that the proposed method achieves detection accuracy which approaches the performance of expert annotators, even with limited amounts of training data.
引用
收藏
页码：1786 / 1789
页数：4
相关论文
共 50 条
  • [1] Tumor Detection In Breast Histopathological Images Using Faster R-CNN
    Harrison, Pratibha
    Park, Kihan
    2021 INTERNATIONAL SYMPOSIUM ON MEDICAL ROBOTICS (ISMR), 2021,
  • [2] Kiwifruit detection in field images using Faster R-CNN with ZFNet
    Fu, Longsheng
    Feng, Yali
    Majeed, Yaqoob
    Zhang, Xin
    Zhang, Jing
    Karkee, Manoj
    Zhang, Qin
    IFAC PAPERSONLINE, 2018, 51 (17): : 45 - 50
  • [3] Detection and classification of COVID-19 by using faster R-CNN and mask R-CNN on CT images
    M. Emin Sahin
    Hasan Ulutas
    Esra Yuce
    Mustafa Fatih Erkoc
    Neural Computing and Applications, 2023, 35 : 13597 - 13611
  • [4] Detection and classification of COVID-19 by using faster R-CNN and mask R-CNN on CT images
    Sahin, M. Emin
    Ulutas, Hasan
    Yuce, Esra
    Erkoc, Mustafa Fatih
    NEURAL COMPUTING & APPLICATIONS, 2023, 35 (18): : 13597 - 13611
  • [5] Using Images Rendered by PBRT to Train Faster R-CNN for UAV Detection
    Peng, Junkai
    Zheng, Changwen
    Lv, Pin
    Cui, Tianyu
    Cheng, Ye
    Si, Lingyu
    26. INTERNATIONAL CONFERENCE IN CENTRAL EUROPE ON COMPUTER GRAPHICS, VISUALIZATION AND COMPUTER VISION (WSCG 2018), 2018, 2802 : 13 - 18
  • [6] PEDESTRIAN DETECTION AT NIGHT BY USING FASTER R-CNN Y INFRARED IMAGES
    Galarza Bravo, Michelle
    Flores Calero, Marco
    INGENIUS-REVISTA DE CIENCIA Y TECNOLOGIA, 2018, (20): : 48 - 57
  • [7] Faster R-CNN for Detection of Carotid Plaque on Ultrasound Images
    An, Xiangjing
    Ye, Guoliang
    Zhou, Xiaoan
    Jiao, Zhibin
    Ding, Shangwei
    Xie, Yanhua
    2019 COMPUTING, COMMUNICATIONS AND IOT APPLICATIONS (COMCOMAP), 2019, : 64 - 69
  • [8] A Lightweight Faster R-CNN for Ship Detection in SAR Images
    Li, Yiding
    Zhang, Shunsheng
    Wang, Wen-Qin
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [9] GFD Faster R-CNN: Gabor Fractal DenseNet Faster R-CNN for Automatic Detection of Esophageal Abnormalities in Endoscopic Images
    Ghatwary, Noha
    Zolgharni, Massoud
    Ye, Xujiong
    MACHINE LEARNING IN MEDICAL IMAGING (MLMI 2019), 2019, 11861 : 89 - 97
  • [10] Face Detection with the Faster R-CNN
    Jiang, Huaizu
    Learned-Miller, Erik
    2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017), 2017, : 650 - 657
12345