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Numan Saeed
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2020 – today
- 2024
- [c14]Fadillah Adamsyah Maani, Anees Ur Rehman Hashmi, Numan Saeed, Mohammad Yaqub:
On Enhancing Brain Tumor Segmentation across Diverse Populations with Convolutional Neural Networks. ISBI 2024: 1-4 - [c13]Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani, Karthik Nandakumar, Mohammad Yaqub:
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network. CaPTion@MICCAI 2024: 231-240 - [c12]Nada Saadi, Numan Saeed, Mohammad Yaqub, Karthik Nandakumar:
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation. MICCAI (12) 2024: 262-271 - [c11]Muhammad Ridzuan, Mai A. Shaaban, Numan Saeed, Ikboljon Sobirov, Mohammad Yaqub:
HuLP: Human-in-the-Loop for Prognosis. MICCAI (5) 2024: 328-338 - [c10]Fadillah Adamsyah Maani, Numan Saeed, Aleksandr Matsun, Mohammad Yaqub:
CoReEcho: Continuous Representation Learning for 2D+Time Echocardiography Analysis. MICCAI (4) 2024: 591-601 - [c9]Numan Saeed, Muhammad Ridzuan, Fadillah Adamsyah Maani, Hussain Alasmawi, Karthik Nandakumar, Mohammad Yaqub:
SurvRNC: Learning Ordered Representations for Survival Prediction Using Rank-N-Contrast. MICCAI (5) 2024: 659-669 - [i19]Fadillah A. Maani, Anees Ur Rehman Hashmi, Mariam Aljuboory, Numan Saeed, Ikboljon Sobirov, Mohammad Yaqub:
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks. CoRR abs/2403.09262 (2024) - [i18]Fadillah Adamsyah Maani, Numan Saeed, Aleksandr Matsun, Mohammad Yaqub:
CoReEcho: Continuous Representation Learning for 2D+time Echocardiography Analysis. CoRR abs/2403.10164 (2024) - [i17]Numan Saeed, Muhammad Ridzuan, Fadillah Adamsyah Maani, Hussain Alasmawi, Karthik Nandakumar, Mohammad Yaqub:
SurvRNC: Learning Ordered Representations for Survival Prediction using Rank-N-Contrast. CoRR abs/2403.10603 (2024) - [i16]Muhammad Ridzuan, Mai Kassem, Numan Saeed, Ikboljon Sobirov, Mohammad Yaqub:
HuLP: Human-in-the-Loop for Prognosis. CoRR abs/2403.13078 (2024) - [i15]Kudaibergen Abutalip, Numan Saeed, Ikboljon Sobirov, Vincent Andrearczyk, Adrien Depeursinge, Mohammad Yaqub:
EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation. CoRR abs/2403.16594 (2024) - [i14]Nada Saadi, Numan Saeed, Mohammad Yaqub, Karthik Nandakumar:
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation. CoRR abs/2404.13704 (2024) - [i13]Fadillah A. Maani, Anees Ur Rehman Hashmi, Numan Saeed, Mohammad Yaqub:
On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural Networks. CoRR abs/2405.02852 (2024) - [i12]Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev, Ibrahim Almakky, Numan Saeed, Mohammad Yaqub:
Continual Learning in Medical Imaging from Theory to Practice: A Survey and Practical Analysis. CoRR abs/2405.13482 (2024) - [i11]Hashmat Shadab Malik, Numan Saeed, Asif Hanif, Muzammal Naseer, Mohammad Yaqub, Salman H. Khan, Fahad Shahbaz Khan:
On Evaluating Adversarial Robustness of Volumetric Medical Segmentation Models. CoRR abs/2406.08486 (2024) - [i10]Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani, Karthik Nandakumar, Mohammad Yaqub:
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network. CoRR abs/2409.19901 (2024) - 2023
- [j1]Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi, Ikboljon Sobirov, Mohammad Yaqub:
MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models. Medical Image Anal. 90: 102989 (2023) - [c8]Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, Sen Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein:
Why is the Winner the Best? CVPR 2023: 19955-19966 - [c7]Kudaibergen Abutalip, Numan Saeed, Mustaqeem Khan, Abdulmotaleb El-Saddik:
Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training. MIDL 2023: 1176-1198 - [c6]Ikboljon Sobirov, Numan Saeed, Mohammad Yaqub:
Super Images - A New 2D Perspective on 3D Medical Imaging Analysis. MIUA 2023: 325-337 - [i9]Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi, Ikboljon Sobirov, Mohammad Yaqub:
MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models. CoRR abs/2304.00774 (2023) - [i8]Kudaibergen Abutalip, Numan Saeed, Mustaqeem Khan, Abdulmotaleb El-Saddik:
Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training. CoRR abs/2304.11445 (2023) - [i7]Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Max Berniker, Ziheng Wang, Rogerio Nespolo, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Bo Liu, David Austin, Yiheng Wang, Michal Futrega, Jean-Francois Puget, Zhenqiang Li, Yoichi Sato, Ryo Fujii, Ryo Hachiuma, Mana Masuda, Hideo Saito, An Wang, Mengya Xu, Mobarakol Islam, Long Bai, Winnie Pang, Hongliang Ren, Chinedu Innocent Nwoye, Luca Sestini, Nicolas Padoy, Maximilian Nielsen, Samuel Schüttler, Thilo Sentker, Hümeyra Husseini, Ivo M. Baltruschat, Rüdiger Schmitz, René Werner, Aleksandr Matsun, Mugariya Farooq, Numan Saeed, Jose Renato Restom Viera, Mohammad Yaqub, Neil Getty, Fangfang Xia, Zixuan Zhao, Xiaotian Duan, Xing Yao, Ange Lou, Hao Yang, Jintong Han, Jack H. Noble, Jie Ying Wu, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Herag Arabian, Ning Ding, Knut Moeller, Weiliang Chen, Quan He, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony M. Jarc:
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge. CoRR abs/2305.07152 (2023) - [i6]Numan Saeed, Muhammad Ridzuan, Roba Al Majzoub, Mohammad Yaqub:
Prompt-based Tuning of Transformer Models for Multi-Center Medical Image Segmentation. CoRR abs/2305.18948 (2023) - [i5]Fadillah A. Maani, Asim Ukaye, Nada Saadi, Numan Saeed, Mohammad Yaqub:
UniLVSeg: Unified Left Ventricular Segmentation with Sparsely Annotated Echocardiogram Videos through Self-Supervised Temporal Masking and Weakly Supervised Training. CoRR abs/2310.00454 (2023) - 2022
- [c5]Numan Saeed, Ikboljon Sobirov, Roba Al Majzoub, Mohammad Yaqub:
TMSS: An End-to-End Transformer-Based Multimodal Network for Segmentation and Survival Prediction. MICCAI (8) 2022: 319-329 - [c4]Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub:
Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models? MIDL 2022: 1005-1018 - [i4]Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub:
Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models? CoRR abs/2201.06086 (2022) - [i3]Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov, Mohammad Yaqub:
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data. CoRR abs/2202.12537 (2022) - [i2]Ikboljon Sobirov, Numan Saeed, Mohammad Yaqub:
Segmentation with Super Images: A New 2D Perspective on 3D Medical Image Analysis. CoRR abs/2205.02847 (2022) - [i1]Numan Saeed, Ikboljon Sobirov, Roba Al Majzoub, Mohammad Yaqub:
TMSS: An End-to-End Transformer-based Multimodal Network for Segmentation and Survival Prediction. CoRR abs/2209.05036 (2022) - 2021
- [c3]Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov, Mohammad Yaqub:
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data. HECKTOR@MICCAI 2021: 278-286
2010 – 2019
- 2016
- [c2]Shahzad Muzaffar, Numan Saeed, Ibrahim M. Elfadel:
Automatic protocol configuration in single-channel low-power dynamic signaling for IoT devices. VLSI-SoC 2016: 1-6 - 2014
- [c1]Muzammil Behzad, Nadeem Javaid, A. Sana, Mahmood Ashraf Khan, Numan Saeed, Zahoor Ali Khan, Umar Qasim:
TSDDR: Threshold Sensitive Density Controlled Divide and Rule Routing Protocol for Wireless Sensor Networks. BWCCA 2014: 78-83
Coauthor Index
aka: Fadillah Adamsyah Maani
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last updated on 2024-11-25 22:48 CET by the dblp team
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