Snake Segmentation of Multiple Sclerosis Lesions for Assisted Diagnosis by Cluster Analysis-Based Techniques

被引:0
|
作者
Bonanno, Lilla [1 ]
Lanzafame, Pietro [1 ]
Celona, Alessandro [1 ]
Marino, Silvia [1 ]
Spano, Barbara [1 ]
Bramanti, Placido [1 ]
Puccio, Luigia
机构
[1] IRCCS Ctr Neurolesi Bonino Pulejo, I-98124 Messina, Italy
关键词
Magnetic Resonance Imaging; Multiple Sclerosis; Snake; Cluster Analysis; GRADIENT VECTOR FLOW; MYOTONIC-DYSTROPHY; MRI FINDINGS;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Magnetic Resonance Imaging (MRI), allowing in-vivo detection of lesions, is today a crucial tool for diagnosis of Multiple Sclerosis (MS). Although the detection of lesions are not sufficient for a diagnosis of MS because of similarity with patterns detected in other neurological diseases, taking into account different radiological informations, MRI findings can often yield a high degree of confidence. We used a snake based procedure for segmentation of lesion then proposing a method based on Cluster Analysis to support clinicians in the diagnosis of MS. By identifying a minimum set of significant descriptors, our algorithm can help neurologist and neuroimaging expert to distinguish MS plaques from other kinds of lesions.
引用
收藏
页码:99 / 110
页数:12
相关论文
共 50 条
  • [41] MULTIPLE-SCLEROSIS - NEW TECHNIQUES IN EARLIER DIAGNOSIS
    HADER, WJ
    CANADIAN FAMILY PHYSICIAN, 1983, 29 (JAN) : 100 - 103
  • [42] A Pattern Analysis-based Segmentation to Localize Early and Late Blight Disease Lesions in Digital Images of Plant Leaves
    Abdu, Aliyu Muhammad
    Mokji, Musa Mohd
    Sheikh, Usman Ullah
    PROCEEDINGS OF THE 2019 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING APPLICATIONS (IEEE ICSIPA 2019), 2019, : 116 - 121
  • [43] Automatic segmentation of white matter and detection of active lesions in multiple sclerosis
    Afzal, H. M. R.
    Luo, S.
    Ramadan, S.
    Lechner-Scott, J.
    MULTIPLE SCLEROSIS JOURNAL, 2018, 24 : 180 - 180
  • [44] Editorial: Automatic methods for multiple sclerosis new lesions detection and segmentation
    Commowick, Olivier
    Combes, Benoit
    Cervenansky, Frederic
    Dojat, Michel
    FRONTIERS IN NEUROSCIENCE, 2023, 17
  • [45] A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI
    Pachai, C
    Zhu, YM
    Grimaud, J
    Hermier, M
    Dromigny-Badin, A
    Boudraa, A
    Gimenez, G
    Confavreux, C
    Froment, JC
    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 1998, 22 (05) : 399 - 408
  • [46] An Automated MRI Segmentation Framework for Brains with Tumors and Multiple Sclerosis Lesions
    Bhanumurthy, Yaswanth M.
    Anne, Koteswararao
    2016 INTERNATIONAL CONFERENCE ON COMPUTATION OF POWER, ENERGY INFORMATION AND COMMUNICATION (ICCPEIC), 2016, : 231 - 236
  • [47] A Cellular Neural Network methodology for the automated segmentation of multiple sclerosis lesions
    Cerasa, Antonio
    Bilotta, Eleonora
    Augimeri, Antonio
    Cherubini, Andrea
    Pantano, Pietro
    Zito, Giancarlo
    Lanza, Pierluigi
    Valentino, Paola
    Gioia, Maria C.
    Quattrone, Aldo
    JOURNAL OF NEUROSCIENCE METHODS, 2012, 203 (01) : 193 - 199
  • [48] Hierarchical segmentation of multiple sclerosis lesions in multi-sequence MRI
    Dugas-Phocion, G
    González, MA
    Lebrun, C
    Chanalet, S
    Bensa, C
    Malandain, G
    Ayache, N
    2004 2ND IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1 AND 2, 2004, : 157 - 160
  • [49] Unsupervised Segmentation for Multiple Sclerosis Lesions in Multimodality Magnetic Resonance Images
    Zeng, Ziming
    Chen, Siping
    Yin, Lidong
    Zwiggelaar, Reyer
    2015 8TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI), 2015, : 126 - 130
  • [50] Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches
    Llado, Xavier
    Oliver, Arnau
    Cabezas, Mariano
    Freixenet, Jordi
    Vilanova, Joan C.
    Quiles, Ana
    Valls, Laia
    Ramio-Torrenta, Lluis
    Rovira, Alex
    INFORMATION SCIENCES, 2012, 186 (01) : 164 - 185