RGB-Based Compressed Medical Imaging Using Sparsity Averaging Reweighted Analysis for Wireless Capsule Endoscopy Images
Compressed medical imaging (CMI) is a medical image sampling process with several samples lower than the Nyquist-Shannon sampling theorem for efficient image sampling; therefore, speeds up the processing time of medical applications. In comparison to previous approaches focusing on single-layer imag...
Enregistré dans:
Auteurs principaux: | Rita Magdalena, Tariq Rahim, I Putu Agus Eka Pratama, Ledya Novamizanti, I Nyoman Apraz Ramatryana, Aamir Younas Raja, Soo Young Shin |
---|---|
Format: | article |
Langue: | EN |
Publié: |
IEEE
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/b2827c88c9b44316a742fec22d7a6d6f |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Physiological Vibration Acceleration (Phybrata) Sensor Assessment of Multi-System Physiological Impairments and Sensory Reweighting Following Concussion
par: Ralston JD, et autres
Publié: (2020) -
Intraoperative Resting-State Functional Connectivity Based on RGB Imaging
par: Charly Caredda, et autres
Publié: (2021) -
Fast Hyperparameter Calibration of Sparsity Enforcing Penalties in Total Generalised Variation Penalised Reconstruction Methods for XCT Using a Planted Virtual Reference Image
par: Stéphane Chrétien, et autres
Publié: (2021) -
Image-Enhanced Capsule Endoscopy Improves the Identification of Small Intestinal Lesions
par: Noriyuki Ogata, et autres
Publié: (2021) -
Multi-Modal Deep Learning for Weeds Detection in Wheat Field Based on RGB-D Images
par: Ke Xu, et autres
Publié: (2021)