3 datasets found
  1. P

    ADAM Dataset

    • paperswithcode.com
    Updated Jun 17, 2023
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    Huihui Fang; Fei Li; Huazhu Fu; Xu sun; Xingxing Cao; Fengbin Lin; Jaemin Son; Sunho Kim; Gwenole Quellec; Sarah Matta; Sharath M Shankaranarayana; Yi-Ting Chen; Chuen-heng Wang; Nisarg A. Shah; Chia-Yen Lee; Chih-Chung Hsu; Hai Xie; Baiying Lei; Ujjwal Baid; Shubham Innani; Kang Dang; Wenxiu Shi; Ravi Kamble; Nitin Singhal; Ching-Wei Wang; Shih-Chang Lo; José Ignacio Orlando; Hrvoje Bogunović; Xiulan Zhang; Yanwu Xu; iChallenge-AMD study group (2023). ADAM Dataset [Dataset]. https://paperswithcode.com/dataset/adam
    Explore at:
    Dataset updated
    Jun 17, 2023
    Authors
    Huihui Fang; Fei Li; Huazhu Fu; Xu sun; Xingxing Cao; Fengbin Lin; Jaemin Son; Sunho Kim; Gwenole Quellec; Sarah Matta; Sharath M Shankaranarayana; Yi-Ting Chen; Chuen-heng Wang; Nisarg A. Shah; Chia-Yen Lee; Chih-Chung Hsu; Hai Xie; Baiying Lei; Ujjwal Baid; Shubham Innani; Kang Dang; Wenxiu Shi; Ravi Kamble; Nitin Singhal; Ching-Wei Wang; Shih-Chang Lo; José Ignacio Orlando; Hrvoje Bogunović; Xiulan Zhang; Yanwu Xu; iChallenge-AMD study group
    Description

    ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA.

    The ADAM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Age-related Macular degeneration (AMD) and segmentation of lesions in fundus photos from AMD patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of AMD on a common dataset of retinal fundus images. We invite the medical image analysis community to participate by developing and testing existing and novel automated fundus classification and segmentation methods.

    Instructions: ADAM: Automatic Detection challenge on Age-related Macular degeneration

    Link: https://amd.grand-challenge.org

    Age-related macular degeneration, abbreviated as AMD, is a degenerative disorder in the macular region. It mainly occurs in people older than 45 years old and its incidence rate is even higher than diabetic retinopathy in the elderly.

    The etiology of AMD is not fully understood, which could be related to multiple factors, including genetics, chronic photodestruction effect, and nutritional disorder. AMD is classified into Dry AMD and Wet AMD. Dry AMD (also called nonexudative AMD) is not neovascular. It is characterized by progressive atrophy of retinal pigment epithelium (RPE). In the late stage, drusen and the large area of atrophy could be observed under ophthalmoscopy. Wet AMD (also called neovascular or exudative AMD), is characterized by active neovascularization under RPE, subsequently causing exudation, hemorrhage, and scarring, and will eventually cause irreversible damage to the photoreceptors and rapid vision loss if left untreated.

    An early diagnosis of AMD is crucial to treatment and prognosis. Fundus photo is one of the basic examinations. The current dataset is composed of AMD and non-AMD (myopia, normal control, etc.) photos. Typical signs of AMD that can be found in these photos include drusen, exudation, hemorrhage, etc.

    The ADAM challenge has 4 tasks:

    Task 1: Classification of AMD and non-AMD fundus images.

    Task 2: Detection and segmentation of optic disc.

    Task 3: Localization of fovea.

    Task 4: Detection and Segmentation of lesions from fundus images.

  2. i

    ADAM: Automatic Detection challenge on Age-related Macular degeneration

    • ieee-dataport.org
    Updated May 11, 2024
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    Huazhu Fu (2024). ADAM: Automatic Detection challenge on Age-related Macular degeneration [Dataset]. http://doi.org/10.21227/dt4f-rt59
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    Dataset updated
    May 11, 2024
    Dataset provided by
    IEEE Dataport
    Authors
    Huazhu Fu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA.The ADAM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Age-related Macular degeneration (AMD) and segmentation of lesions in fundus photos from AMD patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of AMD on a common dataset of retinal fundus images. We invite the medical image analysis community to participate by developing and testing existing and novel automated fundus classification and segmentation methods.

  3. O

    ADAM (Adam: automatic detection challenge on age-related macular...

    • opendatalab.com
    zip
    Updated May 1, 2023
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    Inception Institute of Artificial Intelligence, UAE (2023). ADAM (Adam: automatic detection challenge on age-related macular degeneration) [Dataset]. http://doi.org/10.21227/dt4f-rt59
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 1, 2023
    Dataset provided by
    Inception Institute of Artificial Intelligence, UAE
    Sun Yat-sen University
    Zhongshan Ophthalmic Center, Sun Yat-sen University
    Medical University of Vienna
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA. The ADAM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Age-related Macular degeneration (AMD) and segmentation of lesions in fundus photos from AMD patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of AMD on a common dataset of retinal fundus images. We invite the medical image analysis community to participate by developing and testing existing and novel automated fundus classification and segmentation methods. Instructions: ADAM: Automatic Detection challenge on Age-related Macular degeneration Link: https://amd.grand-challenge.org Age-related macular degeneration, abbreviated as AMD, is a degenerative disorder in the macular region. It mainly occurs in people older than 45 years old and its incidence rate is even higher than diabetic retinopathy in the elderly. The etiology of AMD is not fully understood, which could be related to multiple factors, including genetics, chronic photodestruction effect, and nutritional disorder. AMD is classified into Dry AMD and Wet AMD. Dry AMD (also called nonexudative AMD) is not neovascular. It is characterized by progressive atrophy of retinal pigment epithelium (RPE). In the late stage, drusen and the large area of atrophy could be observed under ophthalmoscopy. Wet AMD (also called neovascular or exudative AMD), is characterized by active neovascularization under RPE, subsequently causing exudation, hemorrhage, and scarring, and will eventually cause irreversible damage to the photoreceptors and rapid vision loss if left untreated. An early diagnosis of AMD is crucial to treatment and prognosis. Fundus photo is one of the basic examinations. The current dataset is composed of AMD and non-AMD (myopia, normal control, etc.) photos. Typical signs of AMD that can be found in these photos include drusen, exudation, hemorrhage, etc. The ADAM challenge has 4 tasks: Task 1: Classification of AMD and non-AMD fundus images. Task 2: Detection and segmentation of optic disc. Task 3: Localization of fovea. Task 4: Detection and Segmentation of lesions from fundus images.

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Share
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Click to copy link
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Close
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Huihui Fang; Fei Li; Huazhu Fu; Xu sun; Xingxing Cao; Fengbin Lin; Jaemin Son; Sunho Kim; Gwenole Quellec; Sarah Matta; Sharath M Shankaranarayana; Yi-Ting Chen; Chuen-heng Wang; Nisarg A. Shah; Chia-Yen Lee; Chih-Chung Hsu; Hai Xie; Baiying Lei; Ujjwal Baid; Shubham Innani; Kang Dang; Wenxiu Shi; Ravi Kamble; Nitin Singhal; Ching-Wei Wang; Shih-Chang Lo; José Ignacio Orlando; Hrvoje Bogunović; Xiulan Zhang; Yanwu Xu; iChallenge-AMD study group (2023). ADAM Dataset [Dataset]. https://paperswithcode.com/dataset/adam

ADAM Dataset

Adam: automatic detection challenge on age-related macular degeneration

Explore at:
Dataset updated
Jun 17, 2023
Authors
Huihui Fang; Fei Li; Huazhu Fu; Xu sun; Xingxing Cao; Fengbin Lin; Jaemin Son; Sunho Kim; Gwenole Quellec; Sarah Matta; Sharath M Shankaranarayana; Yi-Ting Chen; Chuen-heng Wang; Nisarg A. Shah; Chia-Yen Lee; Chih-Chung Hsu; Hai Xie; Baiying Lei; Ujjwal Baid; Shubham Innani; Kang Dang; Wenxiu Shi; Ravi Kamble; Nitin Singhal; Ching-Wei Wang; Shih-Chang Lo; José Ignacio Orlando; Hrvoje Bogunović; Xiulan Zhang; Yanwu Xu; iChallenge-AMD study group
Description

ADAM is organized as a half day Challenge, a Satellite Event of the ISBI 2020 conference in Iowa City, Iowa, USA.

The ADAM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Age-related Macular degeneration (AMD) and segmentation of lesions in fundus photos from AMD patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of AMD on a common dataset of retinal fundus images. We invite the medical image analysis community to participate by developing and testing existing and novel automated fundus classification and segmentation methods.

Instructions: ADAM: Automatic Detection challenge on Age-related Macular degeneration

Link: https://amd.grand-challenge.org

Age-related macular degeneration, abbreviated as AMD, is a degenerative disorder in the macular region. It mainly occurs in people older than 45 years old and its incidence rate is even higher than diabetic retinopathy in the elderly.

The etiology of AMD is not fully understood, which could be related to multiple factors, including genetics, chronic photodestruction effect, and nutritional disorder. AMD is classified into Dry AMD and Wet AMD. Dry AMD (also called nonexudative AMD) is not neovascular. It is characterized by progressive atrophy of retinal pigment epithelium (RPE). In the late stage, drusen and the large area of atrophy could be observed under ophthalmoscopy. Wet AMD (also called neovascular or exudative AMD), is characterized by active neovascularization under RPE, subsequently causing exudation, hemorrhage, and scarring, and will eventually cause irreversible damage to the photoreceptors and rapid vision loss if left untreated.

An early diagnosis of AMD is crucial to treatment and prognosis. Fundus photo is one of the basic examinations. The current dataset is composed of AMD and non-AMD (myopia, normal control, etc.) photos. Typical signs of AMD that can be found in these photos include drusen, exudation, hemorrhage, etc.

The ADAM challenge has 4 tasks:

Task 1: Classification of AMD and non-AMD fundus images.

Task 2: Detection and segmentation of optic disc.

Task 3: Localization of fovea.

Task 4: Detection and Segmentation of lesions from fundus images.

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