Tesis 14220022 Kasiful Aprianto (OPTIMASI SEGMENTASI TUMOR OTAK DENGAN RES-UNET MELALUI MEKANISME ATTENTION DAN QUANTIZATION)

Tesis 14220022 Kasiful Aprianto (OPTIMASI SEGMENTASI TUMOR OTAK DENGAN RES-UNET MELALUI MEKANISME ATTENTION DAN QUANTIZATION)

• By Aprianto, Kasiful;
• Tesis
• 49
• 1-83

Segmentasi citra MRI tumor otak merupakan langkah penting dalam diagnosis dan perencanaan perawatan medis. Penelitian ini mengembangkan model Res-UNet dengan mekanisme attention, seperti attention gate (AG), SE block, dan CBAM, untuk mendeteksi segmentasi tumor otak. Evaluasi dilakukan menggunakan metrik Intersection over Union (IoU), dengan model terbaik mencapai IoU 0.845 setelah dynamic range quantization, ukuran model berkurang 75%, dan waktu inferensi 0.2055 detik per citra. Analisis menunjukkan bahwa tingkat kecerahan memengaruhi hasil segmentasi, di mana dengan perbaikan tingkat kecerahan meningkatkan akurasi pada citra dengan distribusi piksel homogen. Model ini dirancang untuk diterapkan pada perangkat keras dengan keterbatasan sumber daya, seperti di lingkungan rumah sakit. Hasil penelitian membuktikan bahwa Res-UNet dengan mekanisme attention dapat memberikan segmentasi yang akurat dan efisien, dengan potensi besar untuk mendukung diagnosis berbasis citra medis.

• Katakunci Segmentasi tumor otak, Res-UNet, Attention Mechanism, Dynamic range quantization, Intersection over Union (IoU)
• URL https://repository.nusamandiri.ac.id/
• Penerbit Universitas Nusa Mandiri, Jakarta DKI Jakarta

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