Automated Breast Ultrasound for Ductal Pattern Reconstruction: Ground Truth File Generation and CADe Evaluation

被引:0
|
作者
Manousaki, D. [1 ]
Panagiotopoulou, A. [1 ]
Bizimi, V. [2 ]
Haynes, M. S. [3 ]
Love, S. [4 ]
Kallergi, M. [1 ]
机构
[1] TEIA, Dept Biomed Engn, Athens, Greece
[2] Univ Hosp Attikon, Radiol Dept 2, Athens, Greece
[3] JPL, Pasadena, CA USA
[4] Dr Susan Love Res Fdn, Encino, CA USA
关键词
WOMEN;
D O I
10.1088/1742-6596/931/1/012037
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The purpose of this study was the generation of ground truth files (GTFs) of the breast ducts from 3D images of the Invenia (TM) Automated Breast Ultrasound System (ABUS) system (GE Healthcare, Little Chalfont, UK) and the application of these GTFs for the optimization of the imaging protocol and the evaluation of a computer aided detection (CADe) algorithm developed for automated duct detection. Six lactating, nursing volunteers were scanned with the ABUS before and right after breastfeeding their infants. An expert in breast ultrasound generated rough outlines of the milk-filled ducts in the transaxial slices of all image volumes and the final GTFs were created by using thresholding and smoothing tools in ImageJ. In addition, a CADe algorithm automatically segmented duct like areas and its results were compared to the expert's GTFs by estimating true positive fraction (TPF) or % overlap. The CADe output differed significantly from the expert's but both detected a smaller than expected volume of the ducts due to insufficient contrast (ducts were partially filled with milk), discontinuities, and artifacts. GTFs were used to modify the imaging protocol and improve the CADe method. In conclusion, electronic GTFs provide a valuable tool in the optimization of a tomographic imaging system, the imaging protocol, and the CADe algorithms. Their generation, however, is an extremely time consuming, strenuous process, particularly for multi-slice examinations, and alternatives based on phantoms or simulations are highly desirable.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] Automated OCR Ground Truth Generation
    van Beusekom, Joost
    Shafait, Faisal
    Breuel, Thomas M.
    PROCEEDINGS OF THE 8TH IAPR INTERNATIONAL WORKSHOP ON DOCUMENT ANALYSIS SYSTEMS, 2008, : 111 - +
  • [2] Ultrasound evaluation of ductal carcinoma in situ of the breast
    Marco Moschetta
    Angela Sardaro
    Adriana Nitti
    Michele Telegrafo
    Nicola Maggialetti
    Arnaldo Scardapane
    Maria Chiara Brunese
    Valentina Lavelli
    Cristina Ferrari
    Journal of Ultrasound, 2022, 25 : 41 - 45
  • [3] Ultrasound evaluation of ductal carcinoma in situ of the breast
    Moschetta, Marco
    Sardaro, Angela
    Nitti, Adriana
    Telegrafo, Michele
    Maggialetti, Nicola
    Scardapane, Arnaldo
    Brunese, Maria Chiara
    Lavelli, Valentina
    Ferrari, Cristina
    JOURNAL OF ULTRASOUND, 2022, 25 (01) : 41 - 45
  • [4] Unsupervised Ground Truth Generation for Automated Brain EM Image Segmentation
    Roy, Srijita
    Panda, Aditi
    Naskar, Ruchira
    2019 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN), 2019, : 66 - 71
  • [5] GENERATION OF AN ACCURATE FACIAL GROUND TRUTH FOR STEREO ALGORITHM EVALUATION
    Woodward, Alexander
    Leclercq, Philippe
    Detunas, Patrice
    Gimer'farb, Georgy
    COMPUTER VISION AND GRAPHICS (ICCVG 2004), 2006, 32 : 534 - 539
  • [6] Evaluation of automated breast volume scanner for breast conservation surgery in ductal carcinoma in situ
    Huang, Anqian
    Zhu, Luoxi
    Tan, Yanjuan
    Liu, Jian
    Xiang, Jingjing
    Zhu, Qingqing
    Bao, Lingyun
    ONCOLOGY LETTERS, 2016, 12 (04) : 2481 - 2484
  • [7] Automated Ground Truth Generation for Learning-Based Crack Detection on Concrete Surfaces
    Chen, Hsiang-Chieh
    Li, Zheng-Ting
    APPLIED SCIENCES-BASEL, 2021, 11 (22):
  • [8] Development of a Statistical Model for Automated Ground Truth Generation in Low-Resource Languages
    Das S.
    SN Computer Science, 5 (5)
  • [9] Objective evaluation of reconstruction methods for quantitative SPECT imaging in the absence of ground truth
    Jha, Abhinav K.
    Song, Na
    Caffo, Brian
    Frey, Eric C.
    MEDICAL IMAGING 2015: IMAGE PERCEPTION, OBSERVER PERFORMANCE, AND TECHNOLOGY ASSESSMENT, 2015, 9416
  • [10] Ground Truth Generation for Quantitative Performance Evaluation of Localization Methods in Urban Areas
    Takeda, Yuichi
    Tsuchiya, Chikao
    Khiat, Abdelaziz
    2019 30TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV19), 2019, : 1152 - 1158