Computational approach based on deep learning for the classification and segmentation of deep rectosigmoid endometriosis using magnetic resonance images

In: instacron:UFMA · 2025 · W7120588188
dissertation OA: green CC0
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Submitted by Jonathan Sousa de Almeida ([email protected]) on 2025-02-19T17:48:26Z No. of bitstreams: 1 WeslleyKelsonRibeiroFigueredo.pdf: 15219746 bytes, checksum: d4fdfc49ccea8d911146807a2c5a9450 (MD5)

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endometriosis

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