Skin Lesion Diagnosis with Imbalanced ECOC Ensembles

2020 ◽  
pp. 292-303
Author(s):  
Sara Atito Ali Ahmed ◽  
Berrin Yanikoglu ◽  
Cemre Zor ◽  
Muhammad Awais ◽  
Josef Kittler
Keyword(s):  
Skin Lesion

The use of Integra dermal regeneration matrix in the surgical treatment of a recurrent, extensive malignant skin lesion in the temporal region

2013 ◽  
Vol 154 (6) ◽  
pp. 225-227 ◽  
Author(s):  
Csaba Halmy ◽  
Zoltán Nádai ◽  
Krisztián Csőre ◽  
Adrienne Vajda ◽  
Róbert Tamás
Keyword(s):  
Surgical Treatment ◽  
Skin Lesion ◽  
Surgical Management ◽  
Skin Grafting ◽  
Skin Tumor ◽  
Temporal Region ◽  
Aesthetic Result ◽  
Malignant Skin ◽  
Dermal Regeneration Template ◽  
Dermal Regeneration

Authors report on the use of Integra dermal regeneration template after excision of an extended, recurrent skin tumor in the temporal region. The area covered with Integra was 180 cm2. Skin grafting to cover Integra was performed on the 28th day. Both Integra and the skin transplant were taken 100%. Integra dermal regeneration template can provide good functional and aesthetic result in the surgical management of extended skin tumors over the skull. Orv. Hetil., 2013, 154, 225–227.

scholarly journals Adult Female With Upper Extremity Skin Lesion

2021 ◽  
Vol 77 (5) ◽  
pp. 548-560
Author(s):  
Gifford Mezey ◽  
Jacob D. Isserman ◽  
Jonathan E. Davis
Keyword(s):  
Skin Lesion ◽  
Upper Extremity ◽  
Adult Female

scholarly journals FAC-Net: Feedback Attention Network Based on Context Encoder Network for Skin Lesion Segmentation

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5172
Author(s):  
Yuying Dong ◽  
Liejun Wang ◽  
Shuli Cheng ◽  
Yongming Li
Keyword(s):  
Skin Lesion ◽  
Real Life ◽  
Good Deal ◽  
Experimental Tests ◽  
Skin Lesions ◽  
Lesion Segmentation ◽  
Attention Network ◽  
Effective Feedback ◽  
Public Datasets ◽  
Learning Architectures

Considerable research and surveys indicate that skin lesions are an early symptom of skin cancer. Segmentation of skin lesions is still a hot research topic. Dermatological datasets in skin lesion segmentation tasks generated a large number of parameters when data augmented, limiting the application of smart assisted medicine in real life. Hence, this paper proposes an effective feedback attention network (FAC-Net). The network is equipped with the feedback fusion block (FFB) and the attention mechanism block (AMB), through the combination of these two modules, we can obtain richer and more specific feature mapping without data enhancement. Numerous experimental tests were given by us on public datasets (ISIC2018, ISBI2017, ISBI2016), and a good deal of metrics like the Jaccard index (JA) and Dice coefficient (DC) were used to evaluate the results of segmentation. On the ISIC2018 dataset, we obtained results for DC equal to 91.19% and JA equal to 83.99%, compared with the based network. The results of these two main metrics were improved by more than 1%. In addition, the metrics were also improved in the other two datasets. It can be demonstrated through experiments that without any enhancements of the datasets, our lightweight model can achieve better segmentation performance than most deep learning architectures.

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