Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

Marchetti Michael A.; Liopyris Konstantinos; Dusza Stephen W.; Codella Noel C. F.; Gutman David A.; Helba Brian; Kalloo Aadi; Halpern Allan C.; Soyer H. Peter; Curiel-Lewandrowski Clara; Kittler Harald; Caffery Liam; Malvehy Josep; Wellenhof Rainer Hofmann

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Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

机译：计算机算法显示提高皮肤病学家准确性的潜力，以诊断皮肤黑色素瘤：2017年国际皮肤成像协作的结果

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Background: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain.

机译：背景：计算机愿景在图像的皮肤黑色素瘤诊断中有希望，但临床效用是不确定的。

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《Journal of the American Academy of Dermatology》 |2020年第3期|共6页
作者
Marchetti Michael A.; Liopyris Konstantinos; Dusza Stephen W.; Codella Noel C. F.; Gutman David A.; Helba Brian; Kalloo Aadi; Halpern Allan C.; Soyer H. Peter; Curiel-Lewandrowski Clara; Kittler Harald; Caffery Liam; Malvehy Josep; Wellenhof Rainer Hofmann;
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作者单位

Mem Sloan Kettering Canc Ctr Dept Med Dermatol Serv 16 East 60th St New York NY 10022 USA;

Mem Sloan Kettering Canc Ctr Dept Med Dermatol Serv 16 East 60th St New York NY 10022 USA;

Mem Sloan Kettering Canc Ctr Dept Med Dermatol Serv 16 East 60th St New York NY 10022 USA;

Thomas J Watson Res Ctr IBM Res Div Yorktown Hts NY USA;

Emory Univ Sch Med Dept Neurol Atlanta GA 30322 USA;

Kitware Inc Clifton Pk NY USA;

Mem Sloan Kettering Canc Ctr Dept Med Dermatol Serv 16 East 60th St New York NY 10022 USA;

Mem Sloan Kettering Canc Ctr Dept Med Dermatol Serv 16 East 60th St New York NY 10022 USA;

Univ Queensland Dermatol Res Ctr Brisbane Qld Australia;

Univ Arizona Canc Ctr Tucson AZ USA;

Med Univ Vienna Dept Dermatol Vienna Austria;

Univ Queensland Brisbane Qld Australia;

Hosp Clin Barcelona Barcelona Spain;

Med Univ Graz Graz Austria;

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原文格式 PDF
正文语种 eng
中图分类皮肤病学与性病学;
关键词
automated melanoma diagnosis; computer algorithm; computer vision; deep learning; dermatologist; International Skin Imaging Collaboration; International Symposium on Biomedical Imaging; machine learning; melanoma; reader study; skin cancer;

机译：自动黑色素瘤;计算机算法;计算机愿景;深入学习;皮肤科医生;国际皮肤影像学合作;国际生物医学成像研讨会;机器学习;黑色素瘤;读者研究;皮肤癌;皮肤癌;

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专利

1. Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017 [J] . Marchetti Michael A., Liopyris Konstantinos, Dusza Stephen W., Journal of the American Academy of Dermatology . 2020,第3期

机译：计算机算法显示提高皮肤病学家准确性的潜力，以诊断皮肤黑色素瘤：2017年国际皮肤成像协作的结果
2. Dermoscopy Improves the Diagnostic Accuracy of Melanomas Clinically Resembling Seborrheic Keratosis: Cross-Sectional Study of the Ability to Detect Seborrheic Keratosis-Like Melanomas by a Group of Dermatologists with Varying Degrees of Experience [J] . Carrera Cristina, Segura Sonia, Aguilera Paula, Dermatology: international journal for clinical and investigative dermatology . 2017,第6期

机译：Dermoscopy提高了黑色素瘤的诊断准确性，临床上类似脂溢性角化症：横截面研究通过一组具有不同程度的经验的皮肤科医生检测甜甜脉的角化症状黑色素瘤的能力
3. Memetic improved cuckoo search algorithm for automatic B-spline border approximation of cutaneous melanoma from macroscopic medical images [J] . Akemi Galvez, Andres Iglesias Advanced engineering informatics . 2020,第Jana期

机译：模因改进的杜鹃搜索算法，用于从宏观医学图像中自动对皮肤黑素瘤进行B样条边界自动逼近
4. Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC) [C] . Noel C. F. Codella, David Gutman, M. Emre Celebi, IEEE International Symposium on Biomedical Imaging . 2018

机译：用于黑色素瘤检测的皮肤病变分析：由国际皮肤成像合作组织（ISIC）主办的2017年国际生物医学成像研讨会（ISBI）面临的挑战
5. An Algorithm to Improve Deformable Image Registration Accuracy in Challenging Cases of Locally-Advanced Non-Small Cell Lung Cancer [D] . Guy, Christopher Logan 2017

机译：提高局部晚期非小细胞肺癌病例的可变形图像配准精度的算法
6. Results of the 2016 International Skin Imaging Collaboration ISBI Challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images [O] . Michael A. Marchetti, Noel C.F. Codella, Stephen W. Dusza, -1

机译：2016年国际皮肤影像合作组织ISBI挑战的结果：皮肤科医生从皮肤镜图像诊断皮肤黑素瘤的计算机算法的准确性比较
7. Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC) [O] . Codella, Noel C. F., Gutman, David, Celebi, M. Emre, 2018

机译：对黑色素瘤检测的皮肤病变分析：2017年的挑战国际生物医学影像学术研讨会（IsBI），由美国主办国际皮肤影像协作组织（IsIC）

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

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