3D Medical Imaging Segmentation

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

9 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 35 papers with code (41 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• UNETR: Transformers for 3D Medical Image Segmentation
  18 Mar 2021 10 repositories listed
  Inspired by the recent success of transformers for Natural Language Processing (NLP) in long-range sequence learning, we reformulate the task of volumetric (3D) medical image segmentation as a sequence-to-sequence…
• BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis
  7 Apr 2020 8 repositories listed
  This paper describes the field research, design and comparative deployment of a multimodal medical imaging user interface for breast screening.
• Med3D: Transfer Learning for 3D Medical Image Analysis
  1 Apr 2019 7 repositories listed
  The performance on deep learning is significantly affected by volume of training data.
• Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
  9 Jun 2019 4 repositories listed
  Based on automatic deep learning segmentations, we extracted three features which quantify two-dimensional and three-dimensional characteristics of the tumors.
• On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task
  6 Jul 2017 4 repositories listed
  To illustrate its efficiency of learning 3D representation from large-scale image data, the proposed network is validated with the challenging task of parcellating 155 neuroanatomical structures from brain MR images.
• Enforcing temporal consistency in Deep Learning segmentation of brain MR images
  13 Jun 2019 3 repositories listed
  Proposed CNN based segmentation approaches demonstrate how 2D segmentation using prior slices can provide similar results to 3D segmentation while maintaining good continuity in the 3D dimension and improved speed.
• 3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study
  12 Dec 2016 3 repositories listed
  To the best of our knowledge, our work is the first to study subcortical structure segmentation on such large-scale and heterogeneous data.
• LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation Models
  29 Sep 2024 2 repositories listed Syntology ran 10 of 13 samples · 3 unverified · 2 pointer-only (licence)
  To accomplish the above objective, we propose a novel framework named Low-Rank Knowledge Decomposition (LoRKD), which explicitly separates gradients from different tasks by incorporating low-rank expert modules and…
• MIST: A Simple and Scalable End-To-End 3D Medical Imaging Segmentation Framework
  31 Jul 2024 2 repositories listed
  To address this, we introduce the Medical Imaging Segmentation Toolkit (MIST), a simple, modular, and end-to-end medical imaging segmentation framework designed to facilitate consistent training, testing, and evaluation…
• FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images
  14 Mar 2024 2 repositories listed Syntology ran 5 of 12 samples · 7 unverified
  Segment anything models (SAMs) are gaining attention for their zero-shot generalization capability in segmenting objects of unseen classes and in unseen domains when properly prompted.
• Elastic Boundary Projection for 3D Medical Image Segmentation
  3 Dec 2018 2 repositories listed
  The key observation is that, although the object is a 3D volume, what we really need in segmentation is to find its boundary which is a 2D surface.
• AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy
  15 Aug 2018 2 repositories listed
  Methods: Our deep learning model, called AnatomyNet, segments OARs from head and neck CT images in an end-to-end fashion, receiving whole-volume HaN CT images as input and generating masks of all OARs of interest in one…
• Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation
  19 Jul 2018 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  In this paper, we test whether this algorithm, which was shown to improve semantic segmentation for 2D RGB images, is able to improve segmentation quality for 3D multi-modal medical images.
• Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation
  5 Sep 2016 2 repositories listed
  Segmentation of 3D images is a fundamental problem in biomedical image analysis.
• Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation
  18 Mar 2016 2 repositories listed Syntology ran 0 of 12 samples · 12 unverified
  We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation.
• xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba Counterpart
  1 Jul 2024 1 repository listed
  With comprehensive experiments performed, this technical report highlights the potential of xLSTM-based architectures in advancing biomedical image analysis in both 2D and 3D.
• nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model
  5 Feb 2024 1 repository listed
  Extensive experiments on 6 datasets demonstrate nnMamba's superiority over state-of-the-art methods in a suite of challenging tasks, including 3D image segmentation, classification, and landmark detection.
• SegReg: Segmenting OARs by Registering MR Images and CT Annotations
  12 Nov 2023 1 repository listed
  This manual process is highly time-consuming and expensive, limiting the number of patients who can receive timely radiotherapy.
• Reliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis
  17 Oct 2022 1 repository listed
  The segmentations were derived with FreeSurfer from the non-enhanced image and used as ground truth for the coregistered CE image.
• An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation
  10 Jul 2022 1 repository listed
  In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans.
• Dynamic Linear Transformer for 3D Biomedical Image Segmentation
  1 Jun 2022 1 repository listed
  Transformer-based neural networks have surpassed promising performance on many biomedical image segmentation tasks due to a better global information modeling from the self-attention mechanism.
• An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation
  1 Feb 2022 1 repository listed
  The scarcity of pixel-level annotation is a prevalent problem in medical image segmentation tasks.
• Automated Segmentation and Connectivity Analysis for Normal Pressure Hydrocephalus
  10 Jan 2022 1 repository listed
  The segmentation and network features are used to train a model for NPH prediction.
• Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
  5 Nov 2020 1 repository listed
  DL+DiReCT is a promising combination of a deep learning‐based method with a traditional registration technique to detect subtle changes in cortical thickness.
• KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation
  4 Oct 2020 1 repository listed
  To overcome this issue, we propose using an overcomplete convolutional architecture where we project our input image into a higher dimension such that we constrain the receptive field from increasing in the deep layers…
• A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
  12 Aug 2020 1 repository listed
  In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis.
• A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
  11 May 2020 1 repository listed
  Here we present a method for the simultaneous segmentation of white matter lesions and normal-appearing neuroanatomical structures from multi-contrast brain MRI scans of multiple sclerosis patients.
• CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks
  28 Mar 2020 1 repository listed
  3D Convolution Neural Networks (CNNs) have been widely applied to 3D scene understanding, such as video analysis and volumetric image recognition.
• Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation
  1 Sep 2019 1 repository listed
  In conclusion, the proposed CNN-GCN method combines local image information with graph connectivity information, improving pulmonary A/V separation over a baseline CNN method, approaching the performance of human…
• A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
  10 Dec 2018 1 repository listed
  In this paper, we propose a new ensemble learning framework for 3D biomedical image segmentation that combines the merits of 2D and 3D models.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.