Presegmenter Cascaded Framework for Mammogram Mass Segmentation by Urvi Oza, Bakul Gohel, Pankaj Kumar, Parita Oza

“…The presegmenter cascade framework has the potential to improve segmentation performance and mitigate FNs when integrated with any medical image segmentation framework, irrespective of the choice of the model.…”
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Segmentation aware probabilistic phenotyping of single-cell spatial protein expression data by Yuju Lee, Edward L. Y. Chen, Darren C. H. Chan, Anuroopa Dinesh, Somaieh Afiuni-Zadeh, Conor Klamann, Alina Selega, Miralem Mrkonjic, Hartland W. Jackson, Kieran R. Campbell

“…However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. …”
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Multimodal Medical Image Fusion of Positron Emission Tomography and Magnetic Resonance Imaging Using Generative Adversarial Networks by R. Nandhini Abirami, P. M. Durai Raj Vincent, Kathiravan Srinivasan, K. Suresh Manic, Chuan-Yu Chang

“…Multimodal medical image fusion is a current technique applied in the applications related to medical field to combine images from the same modality or different modalities to improve the visual content of the image to perform further operations like image segmentation. Biomedical research and medical image analysis highly demand medical image fusion to perform higher level of medical analysis. …”
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Tuning a SAM-Based Model With Multicognitive Visual Adapter to Remote Sensing Instance Segmentation by Linghao Zheng, Xinyang Pu, Su Zhang, Feng Xu

“…The segment anything model (SAM), a foundational model designed for promptable segmentation tasks, demonstrates exceptional generalization capabilities, making it highly promising for natural scene image segmentation. However, SAM's lack of pretraining on massive remote sensing images and its interactive structure limit its automatic mask prediction capabilities. …”
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Adaptive Learning Algorithms for Low Dose Optimization in Coronary Arteries Angiography: A Comprehensive Review by Komal Tariq, Muhammad Adnan Munir, Hafiza Tooba Aftab, Amir Naveed, Ayesha Yousaf, Sajjad Ul Hassan

“…Results: The extracted data shows a comprehensive data on various techniques that are used for low dose CAA, advancements in image segmentation, noise reduction, and operator dose reduction highlight the potential of machine learning techniques. …”
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A Review of CNN Applications in Smart Agriculture Using Multimodal Data by Mohammad El Sakka, Mihai Ivanovici, Lotfi Chaari, Josiane Mothe

“…Key approaches analyzed involve image classification, image segmentation, regression, and object detection methods that use diverse data types ranging from RGB and multispectral images to radar and thermal data. …”
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Characterization of Vegetation Changes in Jiangsu Coastal Wetlands and Analysis of Their Causes by LYU Lin, YU Lingcheng, QIAN Linfeng, CHEN Yanyan, ZHANG Ke, GU Rong, ZHANG Dong

“…In the paper, using a combination of object-oriented image segmentation and random forest classification, the spatial distribution information of Jiangsu coastal wetland ecosystems in 2011, 2016 and 2021 was extracted based on Landsat and Sentinel-2 satellite images, and the spatiotemporal dynamic changes of the wetland vegetation communities and the causes of wetland vegetation changes were analyzed. …”
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A survey on deep learning for polyp segmentation: techniques, challenges and future trends by Jiaxin Mei, Tao Zhou, Kaiwen Huang, Yizhe Zhang, Yi Zhou, Ye Wu, Huazhu Fu

“…With the advent of deep learning, more and more medical image segmentation algorithms based on deep learning networks have emerged, making significant progress in the field. …”
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MSM-TDE: multi-scale semantics mining and tiny details enhancement network for retinal vessel segmentation by Hongbin Zhang, Jin Zhang, Xuan Zhong, Ya Feng, Guangli Li, Xiong Li, Jingqin Lv, Donghong Ji

“…Abstract Retinal image segmentation is crucial for the early diagnosis of some diseases like diabetes and hypertension. …”
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Features to Text: A Comprehensive Survey of Deep Learning on Semantic Segmentation and Image Captioning by Ariyo Oluwasammi, Muhammad Umar Aftab, Zhiguang Qin, Son Tung Ngo, Thang Van Doan, Son Ba Nguyen, Son Hoang Nguyen, Giang Hoang Nguyen

“…Finally, analysis of the existing methods, their contributions, and relevance are highlighted, informing the importance of these methods and illuminating a possible research continuation for the application of semantic image segmentation and image captioning approaches.…”
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A Novel Diagnostic Aid for Detection of Intra-Abdominal Adhesions to the Anterior Abdominal Wall Using Dynamic Magnetic Resonance Imaging by David Randall, John Fenner, Richard Gillott, Richard ten Broek, Chema Strik, Paul Spencer, Karna Dev Bardhan

“…We describe a technique involving image segmentation and registration to calculate shear as an analogue for visceral slide based on the tracking of structures throughout the respiratory cycle. …”
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Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture by Kushagra Sharma, Shiv Kumar Shivandu

“…DGPS and remote sensing offer precise, real-time data essential for soil condition assessment and crop health monitoring. Advanced image segmentation techniques ensure accurate detection of plants and fruits, overcoming challenges posed by varying lighting conditions and complex backgrounds. …”
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Automated 3D semantic segmentation of PCB X-ray CT images and netlist extraction by Adrian Phoulady, Yara Suleiman, Hongbin Choi, Nicholas May, Sina Shahbazmohamadi, Pouya Tavousi

“…The implications of this approach extend beyond PCBs, finding applications in various physical and biological sciences where 3D image segmentation is crucial. This methodology includes high-resolution 3D imaging, watershed segmentation, machine learning-based semantic segmentation, and netlist extraction. …”
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Method for Identifying Abnormal Hot Spots on the Surface of Composite Insulators by LIU Yao

“…Based on the thermal image segmentation results of composite insulators, pixel statistical methods are used to calculate the horizontal row pixel points of the composite insulator segmentation image and divide the structural area of the composite insulator. …”
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Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision by Yueda Xu, Yanfeng Xing, Hongbo Zhao, Yufang Lin, Lijia Ren, Zhihan Zhou

“…This research focuses on the cell tab, utilizing the hue, saturation, and value (HSV) color space for image segmentation to adaptively extract the cell tab region and further obtain the ROI of the cell tab. …”
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A Real-Time Semantic Segmentation Method of Sheep Carcass Images Based on ICNet by Shida Zhao, Guangzhao Hao, Yichi Zhang, Shucai Wang

“…In addition, we verify the generalization ability of the ICNet for the sheep carcass image dataset by setting different brightness image segmentation experiments. Finally, the U-Net, DeepLabv3, PSPNet, and Fast-SCNN are introduced for comparative experiments to further verify the segmentation performance of the ICNet. …”
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Deep learning-based object detection algorithms in medical imaging: Systematic review by Carina Albuquerque, Roberto Henriques, Mauro Castelli

“…Particularly in medical image analysis, DL received greater attention for tasks like image segmentation, object detection, and classification. …”
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Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data by H. T. Rüdisser, A. Windisch, U. V. Amerstorfer, C. Möstl, T. Amerstorfer, R. L. Bailey, M. A. Reiss

“…For the automatic detection of ICMEs we propose a pipeline using a method that has recently proven successful in medical image segmentation. Comparing it to an existing method, we find that while achieving similar results, our model outperforms the baseline regarding training time by a factor of approximately 20, thus making it more applicable for other datasets. …”
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A Real-Time Road Scene Semantic Segmentation Model Based on Spatial Context Learning by Xiaomei Xiao, Jialiang Tang, Xiaoyan Lu, Zhengyong Feng, Yi Li

“…To address the issues of high computational complexity and insufficient aggregation of global and local information in existing image segmentation methods, this paper proposes an efficient segmentation model based on Spatial Context Learning, named SCLSeg. …”
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Video completion in the presence of moving subjects based on segmentation using Neutrosophic sets by Amanna Ghanbari Talouki, Abbas Koochari, Seyyed Ahmad Edalatpanah

“…The novelty of the approach lies in several key contributions: 1) the use of Neutrosophic theory to handle spatial and intensity uncertainties, 2) a Neutrosophic-based similarity measure for image segmentation, 3) a new metric for finding the most suitable patch for hole filling, and 4) a novel method for preserving boundaries and uniformity in video completion, particularly in the presence of moving objects. …”
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