Search Results - Shigwan, Saurabh J

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  1. 1
    SwinDTI: swin transformer-based generalized fast estimation of diffusion tensor parameters from sparse data

    SwinDTI: swin transformer-based generalized fast estimation of diffusion tensor parameters from sparse data by Tiwari, Abhishek, Singh, Rajeev Kumar, Shigwan, Saurabh J.

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  2. 2
    Object Segmentation with Deep Neural Nets Coupled with a Shape Prior, When Learning From a Training set of Limited Quality and Small Size

    Object Segmentation with Deep Neural Nets Coupled with a Shape Prior, When Learning From a Training set of Limited Quality and Small Size by Shigwan, Saurabh J., Gaikwad, Akshay V., Awate, Suyash P.

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  3. 3
    Deep Learning Framework using Sparse Diffusion MRI for Diagnosis of Frontotemporal Dementia

    Deep Learning Framework using Sparse Diffusion MRI for Diagnosis of Frontotemporal Dementia by Tiwari, Abhishek, Singhal, Ananya, Shigwan, Saurabh J., Kumar Singh, Rajeev

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  4. 4
    Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies

    Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies by Aja-Fernández, Santiago, Martín-Martín, Carmen, Planchuelo-Gómez, Álvaro, Faiyaz, Abrar, Uddin, Md Nasir, Schifitto, Giovanni, Tiwari, Abhishek, Shigwan, Saurabh J., Kumar Singh, Rajeev, Zheng, Tianshu, Cao, Zuozhen, Wu, Dan, Blumberg, Stefano B., Sen, Snigdha, Goodwin-Allcock, Tobias, Slator, Paddy J., Yigit Avci, Mehmet, Li, Zihan, Bilgic, Berkin, Tian, Qiyuan, Wang, Xinyi, Tang, Zihao, Cabezas, Mariano, Rauland, Amelie, Merhof, Dorit, Manzano Maria, Renata, Campos, Vinícius Paraníba, Santini, Tales, da Costa Vieira, Marcelo Andrade, HashemizadehKolowri, SeyyedKazem, DiBella, Edward, Peng, Chenxu, Shen, Zhimin, Chen, Zan, Ullah, Irfan, Mani, Merry, Abdolmotalleby, Hesam, Eckstrom, Samuel, Baete, Steven H., Filipiak, Patryk, Dong, Tanxin, Fan, Qiuyun, de Luis-García, Rodrigo, Tristán-Vega, Antonio, Pieciak, Tomasz

    Published in NeuroImage clinical
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  5. 5
    UnSegMedGAT: Unsupervised Medical Image Segmentation using Graph Attention Networks Clustering

    UnSegMedGAT: Unsupervised Medical Image Segmentation using Graph Attention Networks Clustering by Adityaja, A Mudit, Shigwan, Saurabh J, Kumar, Nitin

    Published in arXiv.org
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  6. 6
    UnSeGArmaNet: Unsupervised Image Segmentation using Graph Neural Networks with Convolutional ARMA Filters

    UnSeGArmaNet: Unsupervised Image Segmentation using Graph Neural Networks with Convolutional ARMA Filters by Kovvuri Sai Gopal Reddy, Saran, Bodduluri, Adityaja, A Mudit, Shigwan, Saurabh J, Kumar, Nitin, Mukherjee, Snehasis

    Published in arXiv.org
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  7. 7
    UnSegGNet: Unsupervised Image Segmentation using Graph Neural Networks

    UnSegGNet: Unsupervised Image Segmentation using Graph Neural Networks by Kovvuri Sai Gopal Reddy, Saran, Bodduluri, Adityaja, A Mudit, Shigwan, Saurabh J, Kumar, Nitin

    Published in arXiv.org
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  8. 8
    Pharmaceutical Analysis of Berberine: An Update

    Pharmaceutical Analysis of Berberine: An Update by Bobade, Preeti S., Ganorkar, Saurabh B., Baviskar, Pragati N., Patil, Nikita B., Shinde, Dhananjay B., Shirkhedkar, Atul A., Chalikwar, Shailesh S.

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  9. 9
    Beyond rankings: Learning (more) from algorithm validation

    Beyond rankings: Learning (more) from algorithm validation by Roß, Tobias, Bruno, Pierangela, Reinke, Annika, Wiesenfarth, Manuel, Koeppel, Lisa, Full, Peter M., Pekdemir, Bünyamin, Godau, Patrick, Trofimova, Darya, Isensee, Fabian, Adler, Tim J., Tran, Thuy N., Moccia, Sara, Calimeri, Francesco, Müller-Stich, Beat P., Kopp-Schneider, Annette, Maier-Hein, Lena

    Published in Medical image analysis
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  10. 10
    Spatially Regularized Shape Analysis of the Hippocampus Using P-Spline Based Shape Regression

    Spatially Regularized Shape Analysis of the Hippocampus Using P-Spline Based Shape Regression by Achterberg, Hakim Christiaan, de Rooi, Johan J., Vernooij, Meike W., Ikram, M. Arfan, Niessen, Wiro J., Eilers, Paul H. C., de Bruijne, Marleen

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