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Papers Blood Cell Detection

“Blood Cell Detection” 태그가 달린 논문 9편 · 필터 해제

Transforming Blood Cell Detection and Classification with Advanced Deep Learning Models: A Comparative Study

2024-10-21 · Shilpa Choudhary, Sandeep Kumar, Pammi Sri Siddhaarth, Guntu Charitasri

Efficient detection and classification of blood cells are vital for accurate diagnosis and effective treatment of blood disorders. This study utilizes a YOLOv10 model trained on Roboflow data with images resized to 640x6…

Blood Cell DetectionCell DetectionClassificationDiagnostic+1

Private, Efficient and Scalable Kernel Learning for Medical Image Analysis

2024-10-21 · Anika Hannemann, Arjhun Swaminathan, Ali Burak Ünal, Mete Akgün

Medical imaging is key in modern medicine. From magnetic resonance imaging (MRI) to microscopic imaging for blood cell detection, diagnostic medical imaging reveals vital insights into patient health. To predict diseases…

Blood Cell DetectionCell DetectionDiagnosticMedical Image Analysis+1

LSM-YOLO: A Compact and Effective ROI Detector for Medical Detection

2024-08-26 · Zhongwen Yu, Qiu Guan, Jianmin Yang, Zhiqiang Yang 외

In existing medical Region of Interest (ROI) detection, there lacks an algorithm that can simultaneously satisfy both real-time performance and accuracy, not meeting the growing demand for automatic detection in medicine…

Blood Cell DetectionCell DetectionDiagnostic

CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer

2023-06-26 · Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël Phan

Blood cell detection is a typical small-scale object detection problem in computer vision. In this paper, we propose a CST-YOLO model for blood cell detection based on YOLOv7 architecture and enhance it with the CNN-Swin…

2D Object DetectionBlood Cell DetectionCell DetectionMedical Diagnosis+6

TE-YOLOF: Tiny and efficient YOLOF for blood cell detection

2021-08-27 · Fanxin Xu, Xiangkui Li, Hang Yang, Yali Wang 외

Blood cell detection in microscopic images is an essential branch of medical image processing research. Since disease detection based on manual checking of blood cells is time-consuming and full of errors, testing of blo…

Blood Cell DetectionCell DetectionObject

Contour Proposal Networks for Biomedical Instance Segmentation

2021-04-07 · Eric Upschulte, Stefan Harmeling, Katrin Amunts, Timo Dickscheid

We present a conceptually simple framework for object instance segmentation called Contour Proposal Network (CPN), which detects possibly overlapping objects in an image while simultaneously fitting closed object contour…

Blood Cell DetectionCell DetectionCell SegmentationInstance Segmentation+6

Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices

2019-09-11 · Tiancheng Xia, Richard Jiang, YongQing Fu, Nanlin Jin

Automated in-vitro cell detection and counting have been a key theme for artificial and intelligent biological analysis such as biopsy, drug analysis and decease diagnosis. Along with the rapid development of microfluidi…

Blood Cell DetectionCell DetectionMedical DiagnosisTransfer Learning

Machine learning approach of automatic identification and counting of blood cells

2019-09-05 · Healthcare Technology Letters, IET 2019 9 · Mohammad Mahmudul Alam, Mohammad Tariqul Islam

A complete blood cell count is an important test in medical diagnosis to evaluate overall health condition. Traditionally blood cells are counted manually using haemocytometer along with other laboratory equipment’s and …

BIG-bench Machine LearningBlood Cell CountBlood Cell DetectionCBC TEST+3

Machine learning approach of automatic identification and counting of blood cells

2019-07-17 · Mohammad Mahmudul Alam, Mohammad Tariqul Islam

A complete blood cell count is an important test in medical diagnosis to evaluate overall health condition. Traditionally blood cells are counted manually using haemocytometer along with other laboratory equipment's and …

BIG-bench Machine LearningBlood Cell CountBlood Cell DetectionMedical Diagnosis+2
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