mlsanityData to 13 Oct 2026

Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images

arXiv 2405.17520 ↗First posted 27 May 2024eess.IV cs.CVcited by 9

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Abstract (arXiv)

Accurate segmentation of anatomical structures and abnormalities in medical images is crucial for computer-aided diagnosis and analysis. While deep learning techniques excel at this task, their computational demands pose challenges. Additionally, some cutting-edge segmentation methods, though effective for general object segmentation, may not be optimised for medical images. To address these issues, we propose Mini-Net, a lightweight segmentation network specifically designed for medical images. With fewer than 38,000 parameters, Mini-Net efficiently captures both high- and low-frequency features, enabling real-time applications in various medical imaging scenarios. We evaluate Mini-Net on various datasets, including DRIVE, STARE, ISIC-2016, ISIC-2018, and MoNuSeg, demonstrating its robustness and good performance compared to state-of-the-art methods.

Key facts. Cited by 9 papers in the map (data through 13 Oct 2026). Builds on 28 of its 63 references that are in the map. First posted on arXiv 27 May 2024.

Builds on

28 of 63 references.

References · 28

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,656
  2. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,287
  3. 2019Searching for MobileNetV3cited by 1,990
  4. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,554
  5. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,522
  6. 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,484
  7. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,475
  8. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,429
  9. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,219
  10. 2018ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Designcited by 1,134
  11. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 664
  12. 2016Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)cited by 197
16 more
  1. 2021UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformercited by 197
  2. 2018Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networkscited by 146
  3. 2018DUNet: A deformable network for retinal vessel segmentationcited by 90
  4. 2019Bi-Directional ConvLSTM U-Net with Densley Connected Convolutionscited by 82
  5. 2017SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentationcited by 49
  6. 2016Deep Retinal Image Understandingcited by 35
  7. 2023AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challengecited by 35
  8. 2018CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentationcited by 34
  9. 2018Retinal vessel segmentation based on Fully Convolutional Neural Networkscited by 25
  10. 2020BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecturecited by 25
  11. 2021Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentationcited by 16
  12. 2022MKIS-Net: A Light-Weight Multi-Kernel Network for Medical Image Segmentationcited by 13
  13. 2023Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentationcited by 10
  14. 2023ESDMR-Net: A Lightweight Network With Expand-Squeeze and Dual Multiscale Residual Connections for Medical Image Segmentationcited by 9
  15. 2022Orientation and Context Entangled Network for Retinal Vessel Segmentationcited by 8
  16. 2020DPN: Detail-Preserving Network with High Resolution Representation for Efficient Segmentation of Retinal Vesselscited by 5

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 5; 2025: 3; 2026: 1.

9 papers.

  1. 2024Region Guided Attention Network for Retinal Vessel Segmentationcited by 4
  2. 2024TESL-Net: A Transformer-Enhanced CNN for Accurate Skin Lesion Segmentationcited by 4
  3. 2024EUIS-Net: A Convolutional Neural Network for Efficient Ultrasound Image Segmentationcited by 4
  4. 2024LSSF-Net: Lightweight Segmentation with Self-Awareness, Spatial Attention, and Focal Modulationcited by 4
  5. 2025Foundation Model for Whole-Heart Segmentation: Leveraging Student-Teacher Learning in Multi-Modal Medical Imagingcited by 2
  6. 2025Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple Sclerosiscited by 1
  7. 2025Focal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentationcited by 1
  8. 2024Adenocarcinoma Segmentation Using Pre-trained Swin-UNet with Parallel Cross-Attention for Multi-Domain Imagingcited by 0
  9. 2026MS-DKC: A Dataset Knowledge Card Framework for Designing and Adapting Medical Image Segmentation Modelscited by 0