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SASAN: ground truth for the effective segmentation and classification of skin cancer using biopsy images.

Sajid KhanMuhammad Asif KhanAdeeb NoorKainat Fareed
Published in: Diagnosis (Berlin, Germany) (2024)
This study highlights the importance of expanding datasets to include challenging scenarios and developing better segmentation methods to enhance automated skin cancer diagnosis. The SASAN dataset serves as a valuable tool for researchers aiming to improve such systems and ultimately contribute to better diagnostic outcomes.
Keyphrases
  • skin cancer
  • deep learning
  • convolutional neural network
  • machine learning
  • climate change
  • adipose tissue
  • high throughput
  • skeletal muscle
  • metabolic syndrome
  • fine needle aspiration
  • insulin resistance
  • weight loss