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All Journal TEKNIK Majalah Ilmiah MOMENTUM Jurnal Rekayasa Mesin Journal of Mechanical Engineering Science and Technology Jurnal Basicedu Journal of Robotics and Control (JRC) Jurnal Abdi Insani Nusantara Science and Technology Proceedings Mechanical Engineering for Society and Industry Jurnal Pengbdian Teknik Mesin Biomedical and Mechanical Engineering Journal Journal of Mechanical Engineering, Science, and Innovation Archive: Jurnal Pengabdian Kepada Masyarakat Jurnal Basicedu JATIMAS : Jurnal Pertanian dan Pengabdian Masyarakat Maddana: Jurnal Pengabdian Kepada Masyarakat AT-TAKLIM: Jurnal Pendidikan Multidisiplin
Wahyu Dwi Lestari
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Journal : Journal of Robotics and Control (JRC)

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Improving Classification Accuracy of Breast Ultrasound Images Using Wasserstein GAN for Synthetic Data Augmentation Mas Diyasa, I Gede Susrama; Humairah, Sayyidah; Puspaningrum, Eva Yulia; Durry, Fara Disa; Lestari, Wahyu Dwi; Caesarendra, Wahyu; Dewi, Deshinta Arrova; Aryananda, Rangga Laksana
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.25075

Abstract

Breast cancer remains one of the most prevalent cancers in Indonesia, and early detection plays a vital role in improving patient outcomes. Ultrasound imaging is a non-invasive and accessible technique used to classify breast conditions into normal, benign, or malignant categories. The advancement of deep learning, particularly Transfer Learning with Convolutional Neural Networks (CNNs), has significantly enhanced the performance of automated image classification. However, the effectiveness of CNNs heavily relies on large, balanced datasets—resources that are often limited and imbalanced in medical domains. To address this issue, this study explores the use of Wasserstein Generative Adversarial Networks (WGAN) for synthetic data augmentation. WGAN is capable of learning the underlying distribution of real ultrasound images and generating high-quality synthetic samples. The inclusion of the Wasserstein distance stabilizes training, with convergence observed around 2500–3000 epochs out of 5000. While synthetic data improves classifier performance, there remains a potential risk of overfitting, particularly when the synthetic images closely mirror the training data. Compared to traditional augmentation techniques such as rotation, flipping, and scaling, WGAN-generated data provides more diverse and realistic representations. Among the tested models, VGG16 achieved the highest accuracy of 83.33% after WGAN augmentation. Nonetheless, computational resource limitations posed challenges in training stability and duration. Furthermore, issues related to model generalizability, as well as ethical and patient privacy considerations in using synthetic medical data, must be addressed to ensure responsible deployment in real-world clinical settings.
Co-Authors Adnyono, Ndaru Ahmad Khairul Faizin Ahmad Khairun Faizin Alfattama, Lona Chinsia Arif Hidayat, Muhammad Aryananda, Rangga Laksana Atika Andini Bayuseno, A P Danaryanto, A T Dera, Nurmala Santi Dewi, Deshinta Arrova Dwi Ari Suryaningrum, Dwi Ari Eva Yulia Puspaningrum Faiza, Linda Ziyadatul Faizin, Ahmad Khairul Fara Disa Durry Fauzan Raka Mawandi Ferdi Kurniawan Firmansah, Achmad Robi Ghozali, Achmad Imam Harya, Gyska Indah Humairah, Sayyidah Ika Nawang Puspitawati Ikhsanudin, Zaky Ishak, Sahional Ismail, R Issafira, Radissa Dzaky Jamari, J Kilo, Faisal Krolczyk, Grzegorz Kurniawan, Ferdi L.Urip Widodo, Yohandrik Novel Karaman Lestari, Mufida Diah Luluk Edahwati Luluk Edahwati Luluk Edahwati Luluk edahwati Mahameru, Rolland D.K. Mahameru, Rolland Darin Khalifah Mahmudah, Imam Mas Diyasa, I Gede Susrama Maulana, Hendra Mawandi, F.R. Mawandi, Fauzan Raka Mirnanda, D. Mirnanda, Dwiky Mr. Sutiyono Muhammad Abdillah Mukti, Abdi Satryo Ndaru Adyono Ndaru Adyono Ndaru Adyono, Ndaru Nikmah, Ulin Novel Karaman Nugroho, A Nunung Lusiana Margawati Nurrokhim, F.H.R. Nurrokhim, Firmansyah Hafizh Rizal Nuryananda, Praja Firdaus Prayoga, Adimas Dwi Radissa Dzaky Issafira Radissa Dzaky Issafira Radissa Dzaky Issafira Radissa Dzaky Issafira Rahardja, Dimas Revindra Rosyadi, Mochammad Wildan Rosyadi, Mochammad Willdan Rosyadi, Willdan Safitri, P.D. Safitri, Puspa Dinda Sanjaya, Kadek Heri Sari, Tria Puspa Seno Darmanto Sri Utami Handayani Suares, Reza Mardiansah Sutiyono Talango, Novriyanti Tjahjono, Jojok Dwirido Tria Puspa Sari Tyas Martika Anggriana Wahyu Caesarendra Widagda, Garda Dibya Widya Kusumaningsih Wiliandi Saputro Wiliandi Saputro Wiliandi Saputro Yanto, Agus Dwi Yudha, Dhian Satria