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Accurate quantification in positron emission tomography (PET) is essential for accurate diagnostic results and effective treatment tracking. A major issue encountered in PET imaging is attenuation. Attenuation refers to the diminution of…

Accurate attenuation and scatter corrections are crucial in positron emission tomography (PET) imaging for accurate visual interpretation and quantitative analysis. Traditional methods relying on computed tomography (CT) or magnetic…

医学物理 · 物理学 2025-11-14 Min Jeong Cho , Hyeong Seok Shim , Sungyu Kim , Jae Sung Lee

Positron Emission Mammography (PEM) imaging systems with the ability in detection of millimeter-sized tumors were developed in recent years. And some of them have been well used in clinical applications. In consideration of biopsy…

In oncology, Positron Emission Tomography imaging is widely used in diagnostics of cancer metastases, in monitoring of progress in course of the cancer treatment, and in planning radiotherapeutic interventions. Accurate and reproducible…

计算机视觉与模式识别 · 计算机科学 2016-11-01 Jakub Czakon , Filip Drapejkowski , Grzegorz Zurek , Piotr Giedziun , Jacek Zebrowski , Witold Dyrka

Positron Emission Tomography (PET) scanners are usually designed with the goal to obtain the best compromise between sensitivity, resolution, field-of-view size, and cost. Therefore, it is difficult to improve the resolution of a PET…

Artificial intelligence (AI) is entering medical imaging, mainly enhancing image reconstruction. Nevertheless, improvements throughout the entire processing, from signal detection to computation, potentially offer significant benefits. This…

机器学习 · 计算机科学 2023-10-27 Stephan Naunheim , Yannick Kuhl , David Schug , Volkmar Schulz , Florian Mueller

MTV is increasingly recognized as an accurate estimate of disease burden, which has prognostic value, but its implementation has been hindered by the time-consuming need for manual segmentation of images. Automated quantitation using…

Breast cancer remains a critical global health challenge, necessitating early and accurate detection for effective treatment. This paper introduces a methodology that combines automated image augmentation selection (RandAugment) with search…

图像与视频处理 · 电气工程与系统科学 2023-11-21 Leon Hamnett , Mary Adewunmi , Modinat Abayomi , Kayode Raheem , Fahad Ahmed

Positron emission tomographs (PET) do not measure an image directly. Instead, they measure at the boundary of the field-of-view (FOV) of PET tomograph a sinogram that consists of measurements of the sums of all the counts along the lines…

The purpose of the presented investigations is to design, construct and establish the characteristic performance of the Jagiellonian Positron Emission Mammography(J-PEM), being designed for the detection and diagnosis of breast cancer. Its…

医学物理 · 物理学 2020-02-19 Shivani , Elżbieta Luczyńska , Sylwia Heinze , Paweł Moskal

Breast cancer is a significant cause of death from cancer in women globally, highlighting the need for improved diagnostic imaging to enhance patient outcomes. Accurate tumour identification is essential for diagnosis, treatment, and…

图像与视频处理 · 电气工程与系统科学 2024-05-15 Chi-en Amy Tai , Alexander Wong

Imaging modalities such as Computed Tomography (CT) and Positron Emission Tomography (PET) are key in cancer detection, inspiring Deep Neural Networks (DNN) models that merge these scans for tumor segmentation. When both CT and PET scans…

图像与视频处理 · 电气工程与系统科学 2024-04-23 Nada Saadi , Numan Saeed , Mohammad Yaqub , Karthik Nandakumar

Breast tumor segmentation is a critical task in computer-aided diagnosis (CAD) systems for breast cancer detection because accurate tumor size, shape and location are important for further tumor quantification and classification. However,…

图像与视频处理 · 电气工程与系统科学 2020-09-29 Bryar Shareef , Alex Vakanski , Min Xian , Phoebe E. Freer

An image restoration approach based on a Bayesian maximum entropy method (MEM) has been applied to a radiological image deconvolution problem, that of reduction of geometric blurring in magnification mammography. The aim of the work is to…

医学物理 · 物理学 2009-11-11 A Jannetta , J C Jackson , C J Kotre , I P Birch , K J Robson , R Padgett

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR…

医学物理 · 物理学 2018-08-01 Kuang Gong , Jaewon Yang , Kyungsang Kim , Georges El Fakhri , Youngho Seo , Quanzheng Li

Positron Emission Tomography (PET) image reconstruction is inherently challenged by Poisson noise and physical degradation factors, which are further exacerbated in limited-angle acquisitions. While deep learning methods demonstrate…

计算机视觉与模式识别 · 计算机科学 2026-05-11 Rüveyda Yilmaz , Yuli Wu , Johannes Stegmaier , Volkmar Schulz

Positron Emission Tomography (PET) is an important clinical imaging tool but inevitably introduces radiation hazards to patients and healthcare providers. Reducing the tracer injection dose and eliminating the CT acquisition for attenuation…

计算机视觉与模式识别 · 计算机科学 2024-06-18 Tianqi Chen , Jun Hou , Yinchi Zhou , Huidong Xie , Xiongchao Chen , Qiong Liu , Xueqi Guo , Menghua Xia , James S. Duncan , Chi Liu , Bo Zhou

Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification. However, attenuation correction is particularly challenging for PET-MRI as neither PET nor…

With the rapid development of deep learning and computer vision technologies, medical image segmentation plays a crucial role in the early diagnosis of breast cancer. However, due to the characteristics of breast ultrasound images, such as…

计算机视觉与模式识别 · 计算机科学 2024-12-24 Jiajun Ding , Beiyao Zhu , Wenjie Wang , Shurong Zhang , Dian Zhua , Zhao Liua

Breast cancer investigation is of great significance, and developing tumor detection methodologies is a critical need. However, it is a challenging task for breast ultrasound due to the complicated breast structure and poor quality of the…

计算机视觉与模式识别 · 计算机科学 2019-10-24 Fei Xu , Yingtao Zhang , Min Xian , H. D. Cheng , Boyu Zhang , Jianrui Ding , Chunping Ning , Ying Wang
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