  Lesion diagnosis of skin lesions is a very challenging task due to high
inter-class similarities and intra-class variations in terms of color, size,
site and appearance among different skin lesions. With the emergence of
computer vision especially deep learning algorithms, lesion diagnosis is made
possible using these algorithms trained on dermoscopic images. Usually, deep
classification networks are used for the lesion diagnosis to determine
different types of skin lesions. In this work, we used pixel-wise
classification network to provide lesion diagnosis rather than classification
network. We propose to use DeeplabV3+ for multi-class lesion diagnosis in
dermoscopic images of Task 3 of ISIC Challenge 2018. We used various
post-processing methods with DeeplabV3+ to determine the lesion diagnosis in
this challenge and submitted the test results.
