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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.10
- 수록면
- 54 - 63 (10page)
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초록· 키워드
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Semantic image segmentation is the process of labeling each image pixel with its associated class label. Most of the image segmentation task use an encoder-decoder-based method, like U-Net and its variants which is a popular strategy for solving segmentation tasks. In this paper, we propose an encoder-decoder-based approach with novel spatial group convolutions (SGC) for skin lesion segmentation. The SGC employ multiple-sized convolution kernels such as 1×1, 3×3, 5×5, 7×7, where each of these k×k kernel operations is decomposed as the combination of k×1 convolution followed by 1×k convolution. The large kernel using two 1-D kernels is likely to have better spatial information of the features and shows the improved model learning with the limited learnable parameters and more discriminative feature extraction. The SGC-based proposed model shows improved segmentation accuracy with a significantly reduced number of model parameters. The mean Jaccard index for the proposed method is 89%, the mean dice score is 93.84%, and the mean accuracy value is 95.99 %, with 0.4 million parameters for the proposed method on the PH2 test dataset.
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참고문헌 (31)
참고문헌 신청
Siegel, R. L. / 2017 / Cancer statistics, 2017 / CA: A Cancer Journal for Clinicians 67(1):730
O. J. Wisco / 2012 / Prognostic factors for melanoma / Dermatologic Clinics 30(3):469~485
M. Balch / 2009 / Final version of 2009 AJCC melanoma staging and classification / J. clinical oncology 27(36):6199~6206
P.Lameski / 2018 / Computer-aided detection of melanoma, a case study / Proceedigns of ETAI 2018, ETAI Society of Macedonia
X. Zhang / 2017 / Melanoma segmentation based on deep learning’ / Computer Assisted Surgery 22:267~277
O. J. Wisco / 2012 / Prognostic factors for melanoma / Dermatologic Clinics 30(3):469~485
M. Balch / 2009 / Final version of 2009 AJCC melanoma staging and classification / J. clinical oncology 27(36):6199~6206
P.Lameski / 2018 / Computer-aided detection of melanoma, a case study / Proceedigns of ETAI 2018, ETAI Society of Macedonia
X. Zhang / 2017 / Melanoma segmentation based on deep learning’ / Computer Assisted Surgery 22:267~277
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