Website: https://www.melba-journal.org
📢 “Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals.”
🖊️ S Sun, S Woerner, A Maier, L M Koch, C F Baumgartner.
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📢 “Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals.”
🖊️ S Sun, S Woerner, A Maier, L M Koch, C F Baumgartner.
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📢 “On the Role of Calibration in Benchmarking Algorithmic Fairness for Skin Cancer Detection.”
🖊️ B Dominique, P Lam, N Kurtansky, J Weber, K Kose, V Rotemberg, J Dy.
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📢 “On the Role of Calibration in Benchmarking Algorithmic Fairness for Skin Cancer Detection.”
🖊️ B Dominique, P Lam, N Kurtansky, J Weber, K Kose, V Rotemberg, J Dy.
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📢 “Circle Representation for Medical Instance Object Segmentation.”
🖊️ J Xiong, E H Nguyen, Y Liu, R Deng, R N Tyree, H Correa, G Hiremath, Y Wang, H Yang, A B Fogo, Y Huo.
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📢 “Circle Representation for Medical Instance Object Segmentation.”
🖊️ J Xiong, E H Nguyen, Y Liu, R Deng, R N Tyree, H Correa, G Hiremath, Y Wang, H Yang, A B Fogo, Y Huo.
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📢 “RAIDER: Rapid, anatomy-independent, deep learning-based PDFF and R2* estimation using magnitude-only signals, dual neural networks and training data distribution design.”
🖊️ T JP Bray, G V Minore, A Bainbridge, L Dwyer-Hemmings, S A Taylor, M A Hall-Craggs, H Zhang.
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📢 “RAIDER: Rapid, anatomy-independent, deep learning-based PDFF and R2* estimation using magnitude-only signals, dual neural networks and training data distribution design.”
🖊️ T JP Bray, G V Minore, A Bainbridge, L Dwyer-Hemmings, S A Taylor, M A Hall-Craggs, H Zhang.
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📢 “AI-CNet3D: An Anatomically-Informed Cross-Attention Network with Multi-Task Consistency Fine-tuning for 3D Glaucoma Classification.”
🖊️ R Kenia, A Li, R Srivastava, K A Thakoor.
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📢 “AI-CNet3D: An Anatomically-Informed Cross-Attention Network with Multi-Task Consistency Fine-tuning for 3D Glaucoma Classification.”
🖊️ R Kenia, A Li, R Srivastava, K A Thakoor.
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📢 “Multi-Domain Brain Vessel Segmentation Through Feature Disentanglement.”
🖊️ F Galati, D Falcetta, R Cortese, F Prados, N Burgos, M A Zuluaga.
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📢 “Multi-Domain Brain Vessel Segmentation Through Feature Disentanglement.”
🖊️ F Galati, D Falcetta, R Cortese, F Prados, N Burgos, M A Zuluaga.
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📢 “Investigating sex bias in ECG classification for Atrial Fibrillation, Sinus Rhythm and Myocardial Infarction.”
🖊️ M Galanty, B van der Ster, A P Vlaar, C I Sánchez.
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📢 “Investigating sex bias in ECG classification for Atrial Fibrillation, Sinus Rhythm and Myocardial Infarction.”
🖊️ M Galanty, B van der Ster, A P Vlaar, C I Sánchez.
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We look forward to working with Julia in her new role as an advisor to the MELBA journal.
We look forward to working with Julia in her new role as an advisor to the MELBA journal.
📢 “Sketchpose: Learning to Segment Cells with Partial Annotations.”
🖊️ @ccazorla31.bsky.social, N Munier, R Morin, P Weiss.
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📢 “Sketchpose: Learning to Segment Cells with Partial Annotations.”
🖊️ @ccazorla31.bsky.social, N Munier, R Morin, P Weiss.
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📢 “SWiFT: Soft-Mask Weight Fine-tuning for Bias Mitigation.”
🖊️ J Yan, F Chen, Y Xue, Y Du, K Vilouras, S A Tsaftaris, S McDonagh.
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📢 “SWiFT: Soft-Mask Weight Fine-tuning for Bias Mitigation.”
🖊️ J Yan, F Chen, Y Xue, Y Du, K Vilouras, S A Tsaftaris, S McDonagh.
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📢 “A Neural Conditional Random Field Model Using Deep Features and Learnable Functions for End-to-End MRI Prostate Zonal Segmentation.”
🖊️ A L Y Hung, K Zhao, K Pang, H Zheng, X Du, Q Miao, D Terzopoulos, K Sung.
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📢 “A Neural Conditional Random Field Model Using Deep Features and Learnable Functions for End-to-End MRI Prostate Zonal Segmentation.”
🖊️ A L Y Hung, K Zhao, K Pang, H Zheng, X Du, Q Miao, D Terzopoulos, K Sung.
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📢 “Robust deformable image registration using synthetic data and transfer learning.”
🖊️ I D Kolenbrander, M Maspero, J PW Pluim.
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📢 “Robust deformable image registration using synthetic data and transfer learning.”
🖊️ I D Kolenbrander, M Maspero, J PW Pluim.
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📢 “Synthetic Data for Robust Stroke Segmentation.”
🖊️ L Chalcroft, I Pappas, C J Price, J Ashburner
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📢 “Synthetic Data for Robust Stroke Segmentation.”
🖊️ L Chalcroft, I Pappas, C J Price, J Ashburner
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📢 “BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023.”
🖊️ A F Kazerooni, N Khalili, X Liu, D Haldar,..., A Resnick, @spyridonbakas.bsky.social, A Vossough, M G Linguraru.
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📢 “BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023.”
🖊️ A F Kazerooni, N Khalili, X Liu, D Haldar,..., A Resnick, @spyridonbakas.bsky.social, A Vossough, M G Linguraru.
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MELBA had the pleasure of hosting the final session of Day 2 at MIDL 2025, featuring two outstanding oral presentations.
This session highlighted the strong synergy between MELBA and MIDL. ⬇️
MELBA had the pleasure of hosting the final session of Day 2 at MIDL 2025, featuring two outstanding oral presentations.
This session highlighted the strong synergy between MELBA and MIDL. ⬇️
📢 “Understanding differences in applying DETR to natural and medical images.”
🖊️ Y Xu, Y Shen, C Fernandez-Granda, L Heacock, K J Geras.
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📢 “Understanding differences in applying DETR to natural and medical images.”
🖊️ Y Xu, Y Shen, C Fernandez-Granda, L Heacock, K J Geras.
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📢 “BrainMorph: A Foundational Keypoint Model for Robust and Flexible Brain MRI Registration.”
🖊️ A Q Wang, R Saluja, H Kim, X He, @adriandalca.bsky.social , @msabuncu.bsky.social.
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📢 “BrainMorph: A Foundational Keypoint Model for Robust and Flexible Brain MRI Registration.”
🖊️ A Q Wang, R Saluja, H Kim, X He, @adriandalca.bsky.social , @msabuncu.bsky.social.
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📢 “MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day.”
🖊️ D Lyu, R Gao, @MariusStaring.
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📢 “MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day.”
🖊️ D Lyu, R Gao, @MariusStaring.
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📢 “How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model.”
🖊️ H Gu, H Dong, J Yang, @MazurowskiPhD (@MazurowskiLab).
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📢 “How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model.”
🖊️ H Gu, H Dong, J Yang, @MazurowskiPhD (@MazurowskiLab).
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We’re excited to welcome three new Associate Editors who bring outstanding expertise in machine learning and biomedical imaging.
Welcome to:
🔹 @bernhardkainz.bsky.social
🔹 @mariavak.bsky.social
🔹 Lisa Koch
We’re thrilled to have you on board! 🚀
We’re excited to welcome three new Associate Editors who bring outstanding expertise in machine learning and biomedical imaging.
Welcome to:
🔹 @bernhardkainz.bsky.social
🔹 @mariavak.bsky.social
🔹 Lisa Koch
We’re thrilled to have you on board! 🚀
We are thrilled to welcome Ismail Ben Ayed as a new Executive Editor of MELBA’s Editorial Board.
With a wealth of experience in #ComputerVision & #BiomedicalImaging, Dr. Ben Ayed will lead us to the next frontier of cutting-edge research.
Stay tuned! 🚀
We are thrilled to welcome Ismail Ben Ayed as a new Executive Editor of MELBA’s Editorial Board.
With a wealth of experience in #ComputerVision & #BiomedicalImaging, Dr. Ben Ayed will lead us to the next frontier of cutting-edge research.
Stay tuned! 🚀
📢 “GeoLS: an Intensity-based, Geodesic Soft Labeling for Image Segmentation.”
🖊️ S Adiga Vasudeva, J Dolz, H Lombaert.
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📢 “GeoLS: an Intensity-based, Geodesic Soft Labeling for Image Segmentation.”
🖊️ S Adiga Vasudeva, J Dolz, H Lombaert.
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📢 “Prompting Medical Large Vision-Language Models to Diagnose Pathologies by Visual Question Answering.”
🖊️ D Guo, D Terzopoulos.
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📢 “Prompting Medical Large Vision-Language Models to Diagnose Pathologies by Visual Question Answering.”
🖊️ D Guo, D Terzopoulos.
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📢 “Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge.”
🖊️ D LaBella, U Baid, O Khanna, S McBurney-Lin, …, J Villanueva-Meyer, A M Rauschecker, A Nada, M Aboian, A E Flanders, B Wiestler, S Bakas, E Calabrese.
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📢 “Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge.”
🖊️ D LaBella, U Baid, O Khanna, S McBurney-Lin, …, J Villanueva-Meyer, A M Rauschecker, A Nada, M Aboian, A E Flanders, B Wiestler, S Bakas, E Calabrese.
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📢 “Learning disentangled representations for unpaired synthesis of high-resolution dynamic MRI.”
🖊️ C Scavinner-Dorval, Rodolphe Bailly, B Borotikar, S Brochard, D Ben Salem, F Rousseau.
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📢 “Learning disentangled representations for unpaired synthesis of high-resolution dynamic MRI.”
🖊️ C Scavinner-Dorval, Rodolphe Bailly, B Borotikar, S Brochard, D Ben Salem, F Rousseau.
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