Classification of Breast Lesions on DCE-MRI Data Using a Fine-Tuned MobileNet

被引：5
|
作者：
Wang, Long [1 ]
Zhang, Ming [1 ]
He, Guangyuan [1 ]
Shen, Dong [1 ]
Meng, Mingzhu [1 ]
机构：
[1] Nanjing Med Univ, Affiliated Changzhou Peoples Hosp 2, Dept Radiol, Changzhou 213164, Peoples R China
来源：
DIAGNOSTICS | 2023年 / 13卷 / 06期
关键词：
mobile convolutional neural networks; deep learning; breast lesions; magnetic resonance imaging; CANCER; DIAGNOSIS; MACHINE; MODEL;
D O I：
10.3390/diagnostics13061067
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
It is crucial to diagnose breast cancer early and accurately to optimize treatment. Presently, most deep learning models used for breast cancer detection cannot be used on mobile phones or low-power devices. This study intended to evaluate the capabilities of MobileNetV1 and MobileNetV2 and their fine-tuned models to differentiate malignant lesions from benign lesions in breast dynamic contrast-enhanced magnetic resonance images (DCE-MRI).
引用
收藏
页数：13
相关论文
共 50 条
  • [1] DCE-MRI interpolation using learned transformations for breast lesions classification
    Hongyu Wang
    Cong Gao
    Jun Feng
    Xiaoying Pan
    Di Yang
    Baoying Chen
    Multimedia Tools and Applications, 2021, 80 : 26237 - 26254
  • [2] DCE-MRI interpolation using learned transformations for breast lesions classification
    Wang, Hongyu
    Gao, Cong
    Feng, Jun
    Pan, Xiaoying
    Yang, Di
    Chen, Baoying
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (17) : 26237 - 26254
  • [3] Improving Brain Tumor MRI Image Classification Prediction based on Fine-tuned MobileNet
    Lu, Quy Thanh
    Nguyen, Triet Minh
    Lam, Huan Le
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2024, 15 (01) : 540 - 550
  • [4] An Investigation of Deep Learning for Lesions Malignancy Classification in Breast DCE-MRI
    Marrone, Stefano
    Piantadosi, Gabriele
    Fusco, Roberta
    Petrillo, Antonella
    Sansone, Mario
    Sansone, Carlo
    IMAGE ANALYSIS AND PROCESSING (ICIAP 2017), PT II, 2017, 10485 : 479 - 489
  • [5] Fine-tuned MobileNet Classifier for Classification of Strawberry and Cherry Fruit Types
    Venkatesh
    Nagaraju, Y.
    Hegde, Siddhanth U.
    Stalin, S.
    2021 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI), 2021,
  • [6] A Multiple Classifier System for Classification of Breast Lesions Using Dynamic and Morphological Features in DCE-MRI
    Fusco, Roberta
    Sansone, Mario
    Petrillo, Antonella
    Sansone, Carlo
    STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION, 2012, 7626 : 684 - 692
  • [7] Breast cancer classification with mammography and DCE-MRI
    Yuan, Yading
    Giger, Maryellen L.
    Li, Hui
    Sennett, Charlene
    MEDICAL IMAGING 2009: COMPUTER-AIDED DIAGNOSIS, 2009, 7260
  • [8] Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI
    Chen, Weijie
    Giger, Maryellen L.
    Bick, Ulrich
    Newstead, Gillian M.
    MEDICAL PHYSICS, 2006, 33 (08) : 2878 - 2887
  • [9] Tumor classification using perfusion volume fractions in breast DCE-MRI
    Lee, Sang Ho
    Kim, Jong Hyo
    Park, Jeong Seon
    Park, Sang Joon
    Jung, Yun Sub
    Song, Jung Joo
    Moon, Woo Kyung
    MEDICAL IMAGING 2008: COMPUTER-AIDED DIAGNOSIS, PTS 1 AND 2, 2008, 6915
  • [10] Differentiating Suspicious Breast Lesions with Ultrafast DCE-MRI
    Pineda, F.
    Easley, T.
    Abe, H.
    Schacht, D.
    Karczmar, G.
    MEDICAL PHYSICS, 2018, 45 (06) : E192 - E192
12345