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Items: 1 to 20 of 227

1.

Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.

Marchetti MA, Codella NCF, Dusza SW, Gutman DA, Helba B, Kalloo A, Mishra N, Carrera C, Celebi ME, DeFazio JL, Jaimes N, Marghoob AA, Quigley E, Scope A, Yélamos O, Halpern AC; International Skin Imaging Collaboration.

J Am Acad Dermatol. 2018 Feb;78(2):270-277.e1. doi: 10.1016/j.jaad.2017.08.016. Epub 2017 Sep 29.

2.

Computer Algorithms Show Potential for Improving Dermatologists' Accuracy to Diagnose Cutaneous Melanoma; Results of ISIC 2017.

Marchetti MA, Liopyris K, Dusza SW, Codella NCF, Gutman DA, Helba B, Kalloo A, Halpern AC; International Skin Imaging Collaboration (ISIC).

J Am Acad Dermatol. 2019 Jul 12. pii: S0190-9622(19)32373-4. doi: 10.1016/j.jaad.2019.07.016. [Epub ahead of print]

PMID:
31306724
3.

Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults.

Ferrante di Ruffano L, Takwoingi Y, Dinnes J, Chuchu N, Bayliss SE, Davenport C, Matin RN, Godfrey K, O'Sullivan C, Gulati A, Chan SA, Durack A, O'Connell S, Gardiner MD, Bamber J, Deeks JJ, Williams HC; Cochrane Skin Cancer Diagnostic Test Accuracy Group.

Cochrane Database Syst Rev. 2018 Dec 4;12:CD013186. doi: 10.1002/14651858.CD013186.

PMID:
30521691
4.

Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults.

Dinnes J, Deeks JJ, Chuchu N, Ferrante di Ruffano L, Matin RN, Thomson DR, Wong KY, Aldridge RB, Abbott R, Fawzy M, Bayliss SE, Grainge MJ, Takwoingi Y, Davenport C, Godfrey K, Walter FM, Williams HC; Cochrane Skin Cancer Diagnostic Test Accuracy Group.

Cochrane Database Syst Rev. 2018 Dec 4;12:CD011902. doi: 10.1002/14651858.CD011902.pub2.

PMID:
30521682
5.

Ugly Duckling Sign as a Major Factor of Efficiency in Melanoma Detection.

Gaudy-Marqueste C, Wazaefi Y, Bruneu Y, Triller R, Thomas L, Pellacani G, Malvehy J, Avril MF, Monestier S, Richard MA, Fertil B, Grob JJ.

JAMA Dermatol. 2017 Apr 1;153(4):279-284. doi: 10.1001/jamadermatol.2016.5500.

PMID:
28196213
6.

Validity and Reliability of Dermoscopic Criteria Used to Differentiate Nevi From Melanoma: A Web-Based International Dermoscopy Society Study.

Carrera C, Marchetti MA, Dusza SW, Argenziano G, Braun RP, Halpern AC, Jaimes N, Kittler HJ, Malvehy J, Menzies SW, Pellacani G, Puig S, Rabinovitz HS, Scope A, Soyer HP, Stolz W, Hofmann-Wellenhof R, Zalaudek I, Marghoob AA.

JAMA Dermatol. 2016 Jul 1;152(7):798-806. doi: 10.1001/jamadermatol.2016.0624.

7.

The performance of SolarScan: an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma.

Menzies SW, Bischof L, Talbot H, Gutenev A, Avramidis M, Wong L, Lo SK, Mackellar G, Skladnev V, McCarthy W, Kelly J, Cranney B, Lye P, Rabinovitz H, Oliviero M, Blum A, Varol A, De'Ambrosis B, McCleod R, Koga H, Grin C, Braun R, Johr R.

Arch Dermatol. 2005 Nov;141(11):1388-96. Erratum in: Arch Dermatol. 2006 May;142(5):558. Virol, Alexandra [corrected to Varol, Alexandra].

PMID:
16301386
8.

Quantitative assessment of tumour extraction from dermoscopy images and evaluation of computer-based extraction methods for an automatic melanoma diagnostic system.

Iyatomi H, Oka H, Saito M, Miyake A, Kimoto M, Yamagami J, Kobayashi S, Tanikawa A, Hagiwara M, Ogawa K, Argenziano G, Soyer HP, Tanaka M.

Melanoma Res. 2006 Apr;16(2):183-90.

PMID:
16567974
9.

Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.

Kaur R, Albano PP, Cole JG, Hagerty J, LeAnder RW, Moss RH, Stoecker WV.

Skin Res Technol. 2015 Nov;21(4):466-73. doi: 10.1111/srt.12216. Epub 2015 Mar 22.

10.

Density-based parallel skin lesion border detection with webCL.

Lemon J, Kockara S, Halic T, Mete M.

BMC Bioinformatics. 2015;16 Suppl 13:S5. doi: 10.1186/1471-2105-16-S13-S5. Epub 2015 Sep 25.

11.

A Clinical Aid for Detecting Skin Cancer: The Triage Amalgamated Dermoscopic Algorithm (TADA).

Rogers T, Marino ML, Dusza SW, Bajaj S, Usatine RP, Marchetti MA, Marghoob AA.

J Am Board Fam Med. 2016 Nov 12;29(6):694-701. doi: 10.3122/jabfm.2016.06.160079.

12.

Melanoma recognition in dermoscopy images using lesion's peripheral region information.

Tajeddin NZ, Asl BM.

Comput Methods Programs Biomed. 2018 Sep;163:143-153. doi: 10.1016/j.cmpb.2018.05.005. Epub 2018 May 8.

PMID:
30119849
13.

Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.

Al-Masni MA, Al-Antari MA, Choi MT, Han SM, Kim TS.

Comput Methods Programs Biomed. 2018 Aug;162:221-231. doi: 10.1016/j.cmpb.2018.05.027. Epub 2018 May 19.

PMID:
29903489
14.

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

Haenssle HA, Fink C, Schneiderbauer R, Toberer F, Buhl T, Blum A, Kalloo A, Hassen ABH, Thomas L, Enk A, Uhlmann L; Reader study level-I and level-II Groups.

Ann Oncol. 2018 Aug 1;29(8):1836-1842. doi: 10.1093/annonc/mdy166.

PMID:
29846502
15.

Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists.

Zortea M, Schopf TR, Thon K, Geilhufe M, Hindberg K, Kirchesch H, Møllersen K, Schulz J, Skrøvseth SO, Godtliebsen F.

Artif Intell Med. 2014 Jan;60(1):13-26. doi: 10.1016/j.artmed.2013.11.006. Epub 2013 Dec 9.

PMID:
24382424
16.

Segmentation of skin lesions in dermoscopy images using fuzzy classification of pixels and histogram thresholding.

Garcia-Arroyo JL, Garcia-Zapirain B.

Comput Methods Programs Biomed. 2019 Jan;168:11-19. doi: 10.1016/j.cmpb.2018.11.001. Epub 2018 Nov 20.

PMID:
30527129
17.

Detection of melanoma from dermoscopic images of naevi acquired under uncontrolled conditions.

Tenenhaus A, Nkengne A, Horn JF, Serruys C, Giron A, Fertil B.

Skin Res Technol. 2010 Feb;16(1):85-97. doi: 10.1111/j.1600-0846.2009.00385.x.

18.

Novel Approaches for Diagnosing Melanoma Skin Lesions Through Supervised and Deep Learning Algorithms.

Premaladha J, Ravichandran KS.

J Med Syst. 2016 Apr;40(4):96. doi: 10.1007/s10916-016-0460-2. Epub 2016 Feb 12.

PMID:
26872778
19.

Melanoma detection by analysis of clinical images using convolutional neural network.

Nasr-Esfahani E, Samavi S, Karimi N, Soroushmehr SM, Jafari MH, Ward K, Najarian K.

Conf Proc IEEE Eng Med Biol Soc. 2016 Aug;2016:1373-1376. doi: 10.1109/EMBC.2016.7590963.

PMID:
28268581
20.

Computer-aided classification of melanocytic lesions using dermoscopic images.

Ferris LK, Harkes JA, Gilbert B, Winger DG, Golubets K, Akilov O, Satyanarayanan M.

J Am Acad Dermatol. 2015 Nov;73(5):769-76. doi: 10.1016/j.jaad.2015.07.028. Epub 2015 Sep 19.

PMID:
26386631

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