ArticleSensors (Basel, Switzerland)2022
Modified U-NET Architecture for Segmentation of Skin Lesion.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- EAAC-Net: An Efficient Adaptive Attention and Convolution Fusion Network for Skin Lesion Segmentation.Journal of imaging informatics in medicine · 2025Article
- Automated liver and spleen segmentation for MR elastography maps using U-Nets.Scientific reports · 2025Article
- ARCUNet: enhancing skin lesion segmentation with residual convolutions and attention mechanisms for improved accuracy and robustness.Scientific reports · 2025Article
- Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model.Scientific reports · 2025Article
- An Enhanced Approach Using AGS Network for Skin Cancer Classification.Sensors (Basel, Switzerland) · 2025Article
- Heterogeneous virus classification using a functional deep learning model based on transmission electron microscopy images.Scientific reports · 2024Article
- Advances in Medical Image Segmentation: A Comprehensive Review of Traditional, Deep Learning and Hybrid Approaches.Bioengineering (Basel, Switzerland) · 2024Review
- Hyperspectral imaging and its applications: A review.Heliyon · 2024Review
- An intelligent LinkNet-34 model with EfficientNetB7 encoder for semantic segmentation of brain tumor.Scientific reports · 2024Article
- HDS-Net: Achieving fine-grained skin lesion segmentation using hybrid encoding and dynamic sparse attention.PloS one · 2024Article
- Gastrointestinal tract disease detection via deep learning based structural and statistical features optimized hexa-classification model.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- A Weakly Supervised Learning Method for Cell Detection and Tracking Using Incomplete Initial Annotations.International journal of molecular sciences · 2023Article
- Content-Based Medical Image Retrieval System for Skin Melanoma Diagnosis Based on Optimized Pair-Wise Comparison Approach.Journal of digital imaging · 2023Article
- Organoids revealed: morphological analysis of the profound next generation in-vitro model with artificial intelligence.Bio-design and manufacturing · 2023Review
- Interpretable Machine Learning Techniques in ECG-Based Heart Disease Classification: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Early and accurate detection of melanoma skin cancer using hybrid level set approach.Frontiers in physiology · 2022Article
- A Secure Framework toward IoMT-Assisted Data Collection, Modeling, and Classification for Intelligent Dermatology Healthcare Services.Contrast media & molecular imaging · 2022Article
- Analysis of Vessel Segmentation Based on Various Enhancement Techniques for Improvement of Vessel Intensity Profile.Computational intelligence and neuroscience · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dermoscopy images can be classified more accurately if skin lesions or nodules are segmented. Because of their fuzzy borders, irregular boundaries, inter- and intra-class variances, and so on, nodule segmentation is a difficult task. For the segmentation of skin lesions from dermoscopic pictures, several algorithms have been developed. However, their accuracy lags well behind the industry standard. In this paper, a modified U-Net architecture is proposed by modifying the feature map's dimension for an accurate and automatic segmentation of dermoscopic images. Apart from this, more kernels to the feature map allowed for a more precise extraction of the nodule. We evaluated the effectiveness of the proposed model by considering several hyper parameters such as epochs, batch size, and the types of optimizers, testing it with augmentation techniques implemented to enhance the amount of photos available in the PH2 dataset. The best performance achieved by the proposed model is with an Adam optimizer using a batch size of 8 and 75 epochs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.