{"list":"other","total":55,"rows":[{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"2304.02643","title":"Segment Anything","created":"2023-04-05","cited_by_count":8234},{"id":"2111.06377","title":"Masked Autoencoders Are Scalable Vision Learners","created":"2021-11-11","cited_by_count":7403},{"id":"1705.07874","title":"A Unified Approach to Interpreting Model Predictions","created":"2017-05-22","cited_by_count":6555},{"id":"1610.02136","title":"A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks","created":"2016-10-07","cited_by_count":2385},{"id":"1807.03888","title":"A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks","created":"2018-07-10","cited_by_count":1485},{"id":"1706.02690","title":"Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks","created":"2017-06-08","cited_by_count":1328},{"id":"2010.03759","title":"Energy-based Out-of-distribution Detection","created":"2020-10-08","cited_by_count":1299},{"id":"2111.09886","title":"SimMIM: A Simple Framework for Masked Image Modeling","created":"2021-11-18","cited_by_count":1153},{"id":"1812.04606","title":"Deep Anomaly Detection with Outlier Exposure","created":"2018-12-11","cited_by_count":942},{"id":"2111.07832","title":"iBOT: Image BERT Pre-Training with Online Tokenizer","created":"2021-11-15","cited_by_count":903},{"id":"2201.01266","title":"Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images","created":"2022-01-04","cited_by_count":830},{"id":"2204.06507","title":"Out-of-Distribution Detection with Deep Nearest Neighbors","created":"2022-04-13","cited_by_count":600},{"id":"2111.12797","title":"ReAct: Out-of-distribution Detection With Rectified Activations","created":"2021-11-24","cited_by_count":486},{"id":"1911.11132","title":"Scaling Out-of-Distribution Detection for Real-World Settings","created":"2019-11-25","cited_by_count":465},{"id":"2211.02701","title":"MONAI: An open-source framework for deep learning in healthcare","created":"2022-11-04","cited_by_count":448},{"id":"1810.09136","title":"Do Deep Generative Models Know What They Don't Know?","created":"2018-10-22","cited_by_count":443},{"id":"2111.14791","title":"Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis","created":"2021-11-29","cited_by_count":422},{"id":"2203.10807","title":"ViM: Out-Of-Distribution with Virtual-logit Matching","created":"2022-03-21","cited_by_count":405},{"id":"2209.09858","title":"Extremely Simple Activation Shaping for Out-of-Distribution Detection","created":"2022-09-20","cited_by_count":212},{"id":"1911.13273","title":"Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation","created":"2019-11-29","cited_by_count":163},{"id":"1506.06448","title":"DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation","created":"2015-06-22","cited_by_count":159},{"id":"2104.03829","title":"Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions","created":"2021-04-08","cited_by_count":68},{"id":"2406.05285","title":"VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging","created":"2024-06-07","cited_by_count":64},{"id":"1612.07003","title":"Image biomarker standardisation initiative","created":"2016-12-21","cited_by_count":63},{"id":"2205.10342","title":"Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)","created":"2022-05-20","cited_by_count":35},{"id":"2107.02568","title":"Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis","created":"2021-07-06","cited_by_count":34},{"id":"2101.03244","title":"End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction","created":"2021-01-08","cited_by_count":32},{"id":"2404.09957","title":"How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model","created":"2024-04-15","cited_by_count":32},{"id":"1908.04126","title":"Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation","created":"2019-08-12","cited_by_count":27},{"id":"2105.07107","title":"An Effective Baseline for Robustness to Distributional Shift","created":"2021-05-15","cited_by_count":25},{"id":"2307.03777","title":"Unsupervised 3D out-of-distribution detection with latent diffusion models","created":"2023-07-07","cited_by_count":22},{"id":"2108.03429","title":"Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation","created":"2021-08-07","cited_by_count":20},{"id":"2310.20271","title":"From Denoising Training to Test-Time Adaptation: Enhancing Domain Generalization for Medical Image Segmentation","created":"2023-10-31","cited_by_count":20},{"id":"2109.08852","title":"Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation","created":"2021-09-18","cited_by_count":16},{"id":"2212.01893","title":"Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering","created":"2022-12-04","cited_by_count":16},{"id":"2304.00212","title":"Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization","created":"2023-04-01","cited_by_count":16},{"id":"2112.12218","title":"Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation","created":"2021-12-22","cited_by_count":13},{"id":"2203.06060","title":"ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI","created":"2022-03-11","cited_by_count":12},{"id":"2206.08222","title":"Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency","created":"2022-06-16","cited_by_count":11},{"id":"2306.13528","title":"Limitations of Out-of-Distribution Detection in 3D Medical Image Segmentation","created":"2023-06-23","cited_by_count":11},{"id":"2210.17398","title":"Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation","created":"2022-10-31","cited_by_count":10},{"id":"2107.13964","title":"Mind the Performance Gap: Examining Dataset Shift During Prospective Validation","created":"2021-07-23","cited_by_count":9},{"id":"2306.04974","title":"Conservative Prediction via Data-Driven Confidence Minimization","created":"2023-06-08","cited_by_count":8},{"id":"2306.14658","title":"Beyond AUROC & co. for evaluating out-of-distribution detection performance","created":"2023-06-26","cited_by_count":7},{"id":"2103.15914","title":"Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data","created":"2021-03-29","cited_by_count":5},{"id":"2507.22418","title":"Aleatoric Uncertainty Medical Image Segmentation Estimation via Flow Matching","created":"2025-07-30","cited_by_count":5},{"id":"2405.03762","title":"Swin transformers are robust to distribution and concept drift in endoscopy-based longitudinal rectal cancer assessment","created":"2024-05-06","cited_by_count":4},{"id":"2107.11822","title":"Distributional Shifts in Automated Diabetic Retinopathy Screening","created":"2021-07-25","cited_by_count":3},{"id":"2403.13113","title":"Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets","created":"2024-03-19","cited_by_count":2},{"id":"2505.10223","title":"Data-Agnostic Augmentations for Unknown Variations: Out-of-Distribution Generalisation in MRI Segmentation","created":"2025-05-15","cited_by_count":2},{"id":"2303.03494","title":"Deep Learning Based Dominant Index Lesion Segmentation for MR-guided Radiation Therapy of Prostate Cancer","created":"2023-03-06","cited_by_count":1},{"id":"2408.02761","title":"Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image Segmentation","created":"2024-08-05","cited_by_count":1}],"next_cursor":null}