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检索条件"任意字段=4th International Conference on Biomedical Signal and Image Processing, ICBIP 2019"

共 321 条记录，以下是1-10 订阅

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icbip 2019 - Proceedings of 2019 4th international conference on biomedical signal and image processing

ICBIP 2019 - Proceedings of 2019 4th International Conferenc...

引用

4th international conference on biomedical signal and image processing, icbip 2019

ISBN: (纸本)9781450372244

the proceedings contain 26 papers. the topics discussed include: Automatic sleep staging based on curriculum learning approach;epileptic seizure classification based on the combined features;application of granger causality in decoding covert selective attention with human EEG;muscle artifacts cancellation framework for ECG signals combining convolution auto-encoder and average beat subtraction;forecasting of ventricular tachyarrhythmia based on multi-scale entropy of short-term heart rate variability;control of upper limb motions by combinations of basic muscle synergies;kinematic characteristics of backhand block in table tennis;and an approach for recognition of enhancer-promoter associations based on random forest.

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Improved Breast Cancer Detection in Ultrasound images Using Masked image Integration and Transfer Learning 4

Improved Breast Cancer Detection in Ultrasound Images Using ...

引用

4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Shuvo, H.M. Maruf Rahman Islam, Md. Nazmul Biswas, Sunirmal Kumar Islam, Md. Shafiqul Dhaka Bangladesh Electrical and Electronic Engineering Prime University Dhaka Bangladesh Biomedical Physics and Technology University of Dhaka Dhaka Bangladesh

ISBN: (纸本)9798331530938

An early diagnosis is essential for the effective treatment of breast cancer, which is one of the most commonly prevalent cancers in women. In this study, we propose a Deep Learning Transfer Learning technique for segmenting breast cancer tumors from Ultrasound images. To enhance efficiency, we also added masked images with the ultrasound images as a novel strategy. Our main goal is to produce better outcomes with fewer images. To begin with, a straightforward CNN model is created to segment the tumors. To segregate the tumors from the ultrasound and masked images, we next examine how well several Pretrained models, including VGG16, ResNet50, XceptionNet, EfficientNetB7, and ConvNeXtBase, perform. Using metrics like as Accuracy, Precision, Recall and F1-score we evaluate each model's performance. Our findings demonstrate that transfer learning-based approaches perform better than the straightforward CNN model in terms of Accuracy and F1-Score, and that using masked images in addition to the ultrasound images enhances performances even more. EfficientNetB7, which has an F1-Score of 0.9750 and an overall Accuracy of 97.50%, is considered the best-performing model. Importantly, our method only requires a modest quantity of training data to produce these outcomes. © 2025 IEEE.

关键词： Ultrasonic imaging

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2019 IEEE 4th international conference on signal and image processing, ICSIP 2019

2019 IEEE 4th International Conference on Signal and Image P...

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4th IEEE international conference on signal and image processing, ICSIP 2019

ISBN: (纸本)9781728136608

the proceedings contain 207 papers. the topics discussed include: design of intelligent acquisition system for tomato leaf area;high-performance convolutional neural network accelerator based on systolic arrays and quantization;adaptive opposition-based particle swarm optimization algorithm and application research;color image quality assessment with multi deep convolutional networks;temporal correlation approach to quality improvement of frame-by-frame localization nanoscopy images;transfer learninng in polytime codes signal recognition;local low-rank approach for despeckling of ocean internal wave on SAR image;and different versions of entropy rate superpixel segmentation for hyperspectral image.

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2019 4th international conference on Intelligent Computing and signal processing, ICSP 2019 - signal and image processing

2019 4th International Conference on Intelligent Computing a...

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2019 4th international conference on Intelligent Computing and signal processing, ICSP 2019

the proceedings contain 409 papers. the topics discussed include: case reasoning based design system for product packaging;research on X-ray welding image defect detection based on convolution neural network;radar imaging based on orthogonal matching pursuit via sparse constraint;global salient object detection based on multiple visual features;improved non-local means algorithm for image denosing;using FFT to reduce the computational complexity of sub-nyquist sampling based wideband spectrum sensing;design of intelligent MAN architecture based on MPLS-VPN;encryption cipher text retrieval scheme based on fully homomorphic encryption enterprise cloud storage;protein secondary structure online server predictive evaluation;and research and design of lightweight workflow engine based on SCA.

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2019 4th international conference on Communication, image and signal processing, CCISP 2019

2019 4th International Conference on Communication, Image an...

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2019 4th international conference on Communication, image and signal processing, CCISP 2019

the proceedings contain 33 papers. the topics discussed include: performance evaluation of channel decoder based on recurrent neural network;detect black box signals with enhanced spectrum and support vector classifier;envelope phase shift feature extraction of underwater target echo;a symmetric successive overrelaxation (SSOR) based Gauss-Seidel massive MIMO detection algorithm;massive MIMO detection algorithms based on MMSE-SIC, ZF-MIC, Neumann series expansion, Gauss-Seidel, and Jacobi method;new secret key agreement scheme over relay communication channel;and optimization of Lucy-Richardson algorithm using modified Tikhonov regularization for image deblurring.

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Improved Breast Cancer Detection in Ultrasound images Using Masked image Integration and Transfer Learning

Improved Breast Cancer Detection in Ultrasound Images Using ...

引用

international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： H.M. Maruf Rahman Shuvo Md. Nazmul Islam Sunirmal Kumar Biswas Md. Shafiqul Islam Electrical Electronic and Communication Engineering Military Institute of Science and Technology (MIST) Dhaka Bangladesh Electrical and Electronic Engineering Prime University Dhaka Bangladesh Biomedical Physics and Technology University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798331530952

ISBN: (纸本)9798331530969

关键词： Deep learning image segmentation Ultrasonic imaging Accuracy Transfer learning Training data signal processing Breast cancer Tumors Testing

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ICBSP 2019 - 2019 4th international conference on biomedical Imaging, signal processing

ICBSP 2019 - 2019 4th International Conference on Biomedical...

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6th international Workshop on Sensor-Based Activity Recognition and Interaction, iWOAR 2019

ISBN: (纸本)9781450377140

the proceedings contain 10 papers. the topics discussed include: the SEBA system: a novel approach for assessing psychological stress continuously at the workplace;an automated assessment system for embodied cognition in children: from motion data to executive functioning;cognitive assessment in children through motion capture and computer vision: the cross-your-body task;'SmartPointer' – buttonless remote control based on structured light and intuitive gestures;towards estimation of cooking complexity: free-text annotations in the kitchen environment;and subject-dependent and -independent human activity recognition with person-specific and -independent models.

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three-dimensional Reconstruction of Optical Coherence Tomography images of Esophagus 19

Three-dimensional Reconstruction of Optical Coherence Tomogr...

引用

4th international conference on biomedical signal and image processing

作者： Nao, Sihan Zhang, Miao Wang, Lirong Xu, Yongjin Chen, Xiaohe Shanghai Univ Sch Mechatron Engn & Automat Shanghai Peoples R China Soochow Univ Sch Elect & Informat Engn Suzhou Peoples R China Chinese Acad Sci Suzhou Inst Biomed Engn & Technol Med Elect Dept Suzhou Peoples R China

ISBN: (纸本)9781450372244

the combination of optical coherence tomography (OCT) and endoscope can take images of the body tissues for clinical diagnosis. OCT images are difficult to photograph with regular imaging devices, such as the esophagus and gastrointestinal tract. three-dimensional reconstruction of the two-dimensional sequence images can help the doctor understand the clinical situation of the body tissue, therefore improve the accuracy of diagnosis. In this paper, Ray Casting method is used to reconstruct three-dimensional image of OCT cross-section images of guinea pig esophagus. Preprocessing including image segmentation, coordinate transformation, angle correction is used to achieve a better result in three-dimensional reconstruction. the performance of the algorithm is discussed and can achieve the same effect as what of commercial software.

关键词： Optical coherence tomography (OCT) three-dimensional reconstruction Ray Casting Computer vision Medical image processing

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Facial Spot Contour Extraction based on Color image processing 19

Facial Spot Contour Extraction based on Color Image Processi...

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4th international conference on biomedical signal and image processing

作者： Liu, Xiaojin Sun, Jiuai Wang, Xiong Univ Shanghai Sci & Technol Sch Med Instrument & Food Engn Shanghai Peoples R China Shanghai Univ Med & Hlth Sci Sch Med Imaging Shanghai Peoples R China Shanghai Sixth Peoples Hosp East Hosp Dermatol Dept Shanghai Peoples R China

ISBN: (纸本)9781450372244

In this paper we discuss the problem of automatic contour extraction of facial spot based on RGB images. Prior similar work has been frequently used for processing those hyperpigmentation skin conditions such as melasma and melanoma, where the separation between pigmented area and normal skin is easy to define. However the melanin under facial spots is normally deposited in a scatter way and distributed superficially, this makes the contrast between the area of spots and that of normal skin become small. As such it is difficult to directly extract the contour of the spots. After analyzing the individual three color channels of facial spot RGB skin image, we found that the blue channel provides the clearest edge of the spots, while the edge presents a certain amount of blur in the red channel. therefore, this study proposed a new image processing strategy for facial spots analysis, i.e. to firstly separate the RGB channels to obtain the blue channel, then, the maximum entropy threshold segmentation and the Snake method are used to extract the contour of color spots. the experiments verified that the separated color channel and Snake-based method can help to reliably extract edge contours and preserve the color information of the spot.

关键词： Snake algorithm Edge detection Contour extraction Color image analysis White balance

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Computer-aided Cervical Cancer Screening Method based on Multi-spectral Narrow-band Imaging 19

Computer-aided Cervical Cancer Screening Method based on Mul...

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4th international conference on biomedical signal and image processing

作者： Yang, Zihan Yi, Dingrong Shen, Jiahao Huaqiao Univ Coll Mech Engn & Automat Xiamen Fujian Peoples R China

ISBN: (纸本)9781450372244

the contrast of white colposcopy images is low, which is not conducive to the computer assisted identification of different degrees of diseased tissue. In order to improve the sampling accuracy under the image guidance of colposcopy, in this paper, we propose a Computer-aided cervical cancer screening method based on Multi-spectral Narrow-Band Imaging (CMNBI). We sequentially get images of cervical tissue under different illumination sources including white light, narrow-band blue light at a center wavelength of 415nm, and narrow-band green light at a center wavelength of 540nm. the multi-spectral pathology diagnosis methods consist of two stages: the first one is image preprocessing and the other is tissue classification. the image preprocessing algorithm consists of the following steps: First, we perform filtering process on three modes of images to remove noises. Secondly, the sequentially obtained images are spatially co-registered. thirdly, the multiple narrow-band spectral images are fused. In the stage of tissue classification, a two-class Kmeans clustering algorithm is used, using clinics manually identified diseased region as the seed points. To eliminate strong specular reflection points of cervical tissue, we then applied improved K-means clustering algorithm combined with contour coefficient method to improve robustness of the proposed computer-aided cervical cancer screening method. To evaluate the proposed method, we apply the method to both the fused narrow-band multispectral images as well as the conventional white light images. As a result, the sensitivity, specificity and accuracy of CMNBI are all improved with the fused narrow-band multispectral images over that of the conventional white light images.

关键词： Computer-aided diagnosis Cervical cancer screening Narrow-band multi-spectral imaging Multi-band image fusion K-means clustering

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