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segmented ground truth masks  (Kaggle Inc)

 
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    Kaggle Inc segmented ground truth masks
    Fig. 1. Sample montgomery county chest x-ray images and their corresponding <t>ground</t> <t>truth</t> <t>masks.</t>
    Segmented Ground Truth Masks, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/segmented ground truth masks/product/Kaggle Inc
    Average 86 stars, based on 1 article reviews
    segmented ground truth masks - by Bioz Stars, 2026-06
    86/100 stars

    Images

    1) Product Images from "Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks"

    Article Title: Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks

    Journal: Computer Methods and Programs in Biomedicine Update

    doi: 10.1016/j.cmpbup.2025.100211

    Fig. 1. Sample montgomery county chest x-ray images and their corresponding ground truth masks.
    Figure Legend Snippet: Fig. 1. Sample montgomery county chest x-ray images and their corresponding ground truth masks.

    Techniques Used:

    Fig. 2. Sample shenzhen hospital chest x-ray images and their corresponding ground truth masks.
    Figure Legend Snippet: Fig. 2. Sample shenzhen hospital chest x-ray images and their corresponding ground truth masks.

    Techniques Used:

    Fig. 15. Sample MC predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
    Figure Legend Snippet: Fig. 15. Sample MC predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Techniques Used:

    Fig. 16. Sample failed SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
    Figure Legend Snippet: Fig. 16. Sample failed SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Techniques Used:

    Fig. 17. Sample successful SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
    Figure Legend Snippet: Fig. 17. Sample successful SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Techniques Used:



    Similar Products

    segmented ground truth masks  (Kaggle Inc)
    86
    Kaggle Inc segmented ground truth masks
    Fig. 1. Sample montgomery county chest x-ray images and their corresponding <t>ground</t> <t>truth</t> <t>masks.</t>
    Segmented Ground Truth Masks, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/segmented ground truth masks/product/Kaggle Inc
    Average 86 stars, based on 1 article reviews
    segmented ground truth masks - by Bioz Stars, 2026-06
    86/100 stars
    		  Buy from Supplier

    Image Search Results


    Fig. 1. Sample montgomery county chest x-ray images and their corresponding ground truth masks.

    Journal: Computer Methods and Programs in Biomedicine Update

    Article Title: Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks

    doi: 10.1016/j.cmpbup.2025.100211

    Figure Lengend Snippet: Fig. 1. Sample montgomery county chest x-ray images and their corresponding ground truth masks.

    Article Snippet: The second dataset, the Shenzhen Hospital (SH) CXR Dataset [28] comprises 566 chest X-ray images with manually segmented ground truth masks obtained from Kaggle [29–32].

    Techniques:

    Fig. 2. Sample shenzhen hospital chest x-ray images and their corresponding ground truth masks.

    Journal: Computer Methods and Programs in Biomedicine Update

    Article Title: Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks

    doi: 10.1016/j.cmpbup.2025.100211

    Figure Lengend Snippet: Fig. 2. Sample shenzhen hospital chest x-ray images and their corresponding ground truth masks.

    Article Snippet: The second dataset, the Shenzhen Hospital (SH) CXR Dataset [28] comprises 566 chest X-ray images with manually segmented ground truth masks obtained from Kaggle [29–32].

    Techniques:

    Fig. 15. Sample MC predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Journal: Computer Methods and Programs in Biomedicine Update

    Article Title: Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks

    doi: 10.1016/j.cmpbup.2025.100211

    Figure Lengend Snippet: Fig. 15. Sample MC predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: The second dataset, the Shenzhen Hospital (SH) CXR Dataset [28] comprises 566 chest X-ray images with manually segmented ground truth masks obtained from Kaggle [29–32].

    Techniques:

    Fig. 16. Sample failed SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Journal: Computer Methods and Programs in Biomedicine Update

    Article Title: Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks

    doi: 10.1016/j.cmpbup.2025.100211

    Figure Lengend Snippet: Fig. 16. Sample failed SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: The second dataset, the Shenzhen Hospital (SH) CXR Dataset [28] comprises 566 chest X-ray images with manually segmented ground truth masks obtained from Kaggle [29–32].

    Techniques:

    Fig. 17. Sample successful SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Journal: Computer Methods and Programs in Biomedicine Update

    Article Title: Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks

    doi: 10.1016/j.cmpbup.2025.100211

    Figure Lengend Snippet: Fig. 17. Sample successful SH predictions showing the segmented lung boundaries of both the ground truth masks (red) and the predicted one using the proposed DDRU-Net method (blue). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

    Article Snippet: The second dataset, the Shenzhen Hospital (SH) CXR Dataset [28] comprises 566 chest X-ray images with manually segmented ground truth masks obtained from Kaggle [29–32].

    Techniques: