Automated Melanoma Recognition

By Harald Ganster, Axel Pinz, Reinhard Röhrer, Ernst Wildling, Michael Binder, Harald Kittler. IEEE Trans. Medical Imaging, 2001

404 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Media Technology, Oncology

View Paper: https://www.semanticscholar.org/paper/21af8221a8401fff033447b369f6c040288cf6f4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Industrial and Manufacturing Engineering

1. Rafael Padilla
2. Sergio L. Netto
3. Eduardo A. B. da Silva

In Media Technology

1. M. Emre Celebi
2. Noel C. F. Codella

In Oncology

1. Allan Halpern
2. Noel C. F. Codella
3. Brian Helba
4. Lucy R. Chai

Citations in the corpus

• A Comparative Analysis of Object Detection Metrics with a Companion Open-Source Toolkit (2021, background): “Later on, advancements in object detection techniques led to their increasing adoption in areas that included the manufacturing industry with optical inspections [13], video surveillance [14], forensics [15,16], medical image analysis [17–19], autonomous vehicles [20], and traffic monitoring [21].”
• 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) (2016, background): “improvement related to an increase in diagnostic sensitivity [5]–[10].”