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  1. Article ; Online: Robust Coffee Rust Detection Using UAV-Based Aerial RGB Imagery

    Rodriguez-Gallo, Yakdiel / Escobar-Benitez, Byron / Rodriguez-Lainez, Jony

    AgriEngineering. 2023 Aug. 21, v. 5, no. 3 p.1415-1431

    2023  

    Abstract: Timely detection of pests and diseases in crops is essential to mitigate severe damage and economic losses, especially in the context of climate change. This paper describes a method for detecting the presence of coffee leaf rust (CLR) using two ... ...

    Abstract Timely detection of pests and diseases in crops is essential to mitigate severe damage and economic losses, especially in the context of climate change. This paper describes a method for detecting the presence of coffee leaf rust (CLR) using two databases: RoCoLe and a database obtained from an unmanned aerial vehicle (UAV) equipped with an RGB camera. The developed method follows a two-stage approach. In the first stage, images are processed using ImageJ software, while, in the second phase, Python is used to implement morphological filters and the Hough transform for rust identification. The algorithm’s performance is evaluated using the chi-square test, and its discriminatory capacity is assessed through the generation of a Receiver Operating Characteristic (ROC) curve. Additionally, Cohen’s kappa method is used to assess the agreement among observers, while Kendall’s rank correlation coefficient (KRCC) measures the correlation between the criteria of the observers and the classifications generated by the method. The results demonstrate that the developed method achieved an efficiency of 97% in detecting coffee rust in the RoCoLe dataset and over 93.5% in UAV images. These findings suggest that the developed method has the potential to be implemented in the future on a UAV for rust detection.
    Keywords algorithms ; cameras ; chi-square distribution ; climate change ; computer software ; data collection ; databases ; leaf rust ; unmanned aerial vehicles
    Language English
    Dates of publication 2023-0821
    Size p. 1415-1431.
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ISSN 2624-7402
    DOI 10.3390/agriengineering5030088
    Database NAL-Catalogue (AGRICOLA)

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  2. Article ; Online: Inpainting-filtering for metal artifact reduction (IMIF-MAR) in computed tomography.

    Rodríguez-Gallo, Yakdiel / Orozco-Morales, Rubén / Pérez-Díaz, Marlen

    Physical and engineering sciences in medicine

    2021  Volume 44, Issue 2, Page(s) 409–423

    Abstract: The reduction of metal artifacts remains a challenge in computed tomography because they decrease image quality, and consequently might affect the medical diagnosis. The objective of this study is to present a novel method to correct metal artifacts ... ...

    Abstract The reduction of metal artifacts remains a challenge in computed tomography because they decrease image quality, and consequently might affect the medical diagnosis. The objective of this study is to present a novel method to correct metal artifacts based solely on the CT-slices. The proposed method consists of four steps. First, metal implants in the original CT-slice are segmented using an entropy based method, producing a metal image. Second, a prior image is acquired using three transformations: Gaussian filter, Parisotto and Schoenlieb inpainting method with the Mumford-Shah image model and L0 Gradient Minimization method (L0GM). Next, based on the projections from the original CT-slice, prior image and metal image, the sinogram is corrected in the traces affected by metal in the process called normalization and denormalization. Finally, the reconstructed image is obtained by FBP and a Nonlocal Means (NLM) filtering. The efficacy of the algorithm is evaluated by comparing five image quality metrics of the images and by inspecting regions of interest (ROI). Phantom data as well as clinical datasets are included. The proposed method is compared with three established metal artifact reduction (MAR) methods. The results from a phantom and clinical dataset show the visible reduction of artifacts. The conclusion is that IMIF-MAR method can reduce streak metal artifacts effectively and avoid new artifacts around metal implants, while preserving the anatomical structures. Considering both clinical and phantom studies, the proposed MAR algorithm improves the quality of clinical images affected by metal artifacts, and could be integrated in clinical setting.
    MeSH term(s) Algorithms ; Artifacts ; Metals ; Phantoms, Imaging ; Tomography, X-Ray Computed
    Chemical Substances Metals
    Language English
    Publishing date 2021-03-24
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2662-4737
    ISSN (online) 2662-4737
    DOI 10.1007/s13246-021-00990-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Analysis of objective quality metrics in computed tomography images affected by metal artifacts.

    Rodriguez-Gallo, Yakdiel / Orozco-Morales, Ruben / Marlen Perez-Diaz

    Biomedizinische Technik. Biomedical engineering

    2021  Volume 67, Issue 1, Page(s) 1–9

    Abstract: Image quality (IQ) assessment plays an important role in the medical world. New methods to evaluate image quality have been developed, but their application in the context of computer tomography is yet limited. In this paper the performance of fifteen ... ...

    Abstract Image quality (IQ) assessment plays an important role in the medical world. New methods to evaluate image quality have been developed, but their application in the context of computer tomography is yet limited. In this paper the performance of fifteen well-known full reference (FR) IQ metrics is compared with human judgment using images affected by metal artifacts and processed with metal artifact reduction methods from a phantom. Five region of interest with different sizes were selected. IQ was evaluated by seven experienced radiologists completely blinded to the information. To measure the correlation between FR-IQ, and the score assigned by radiologists non-parametric Spearman rank-order correlation coefficient and Kendall's Rank-order Correlation coefficient were used; so as root mean square error and the mean absolute error to measure the prediction accuracy. Cohen's kappa was employed with the purpose of assessing inter-observer agreement. The metrics GMSD, IWMSE, IWPSNR, WSNR and OSS-PSNR were the best ranked. Inter-observer agreement was between 0.596 and 0.954, with p<0.001 in all study. The objective scores predicted by these methods correlate consistently with the subjective evaluations. The application of this metrics will make possible a better evaluation of metal artifact reduction algorithms in future works.
    MeSH term(s) Algorithms ; Artifacts ; Benchmarking ; Humans ; Phantoms, Imaging ; Tomography, X-Ray Computed
    Language English
    Publishing date 2021-12-28
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 120817-2
    ISSN 1862-278X ; 0013-5585
    ISSN (online) 1862-278X
    ISSN 0013-5585
    DOI 10.1515/bmt-2020-0244
    Database MEDical Literature Analysis and Retrieval System OnLINE

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