20.13.3 Medical Applications -- Cervical Cancer Analysis, Ovarian Cancer

Chapter Contents (Back)
Cervical Cancer. Ovarian Cancer. Cancer Detection.

Oliver, L.H., Poulsen, R.S., Toussaint, G.T., Louis, C.,
Classification of atypical cells in the automatic cytoscreening for cervical cancer,
PR(11), No. 3, 1979, pp. 205-212.
WWW Link. 0309
BibRef

Bengtsson, E., Eriksson, O., Holmquist, J., Jarkrans, T., Nordin, B., Stenkvist, B.,
Segmentation of Cervical Cells: Detection of Overlapping Cell Nuclei,
CGIP(16), No. 4, August 1981, pp. 382-394.
WWW Link. BibRef 8108

Goerttler, K., Stoehr, M., Ploem, J., Bloss, W.H.,
Requirements for Sequential Flow and Static Image Analysis: A Preliminary Study,
PR(13), No. 4, 1981, pp. 279-283.
WWW Link. 0309
The hybridization of flow and image analysis in the prescreening of gynecological smears combines the advantages of both methods. BibRef

Zahniser, D.J.,
Automation of Pap Smear Analysis: A Review and Status Report,
PDA83(265-294). BibRef 8300

Lin, Y.K., and Fu, K.S.,
Automatic Classification of Cervical Cells Using a Binary Tree Classifier,
PR(16), No. 1, 1983, pp. 69-80.
WWW Link. BibRef 8300

Nguyen, N.G., Poulsen, R.S., Louis, C.,
Some New Color Features and Their Application to Cervical Cell Classification,
PR(16), No. 4, 1983, pp. 401-411.
WWW Link. BibRef 8300

Ji, Q.A.[Qi-Ang], Engel, J.[John], Craine, E.[Eric],
Classifying cervix tissue patterns with texture analysis,
PR(33), No. 9, September 2000, pp. 1561-1573.
WWW Link. 0005
BibRef

Ji, Q., Engel, J., Craine, E.,
Texture analysis for classification of cervix lesions,
MedImg(19), No. 11, November 2000, pp. 1144-1149.
IEEE Top Reference. 0110
BibRef

Potonik, B.[Boidar], Zazula, D.[Damjan],
Automated analysis of a sequence of ovarian ultrasound images. Part I: Segmentation of single 2D images,
IVC(20), No. 3, March 2002, pp. 217-225.
WWW Link. 0202
BibRef

Potonik, B.[Boidar], Zazula, D.[Damjan],
Automated analysis of a sequence of ovarian ultrasound images. Part II: Prediction-based object recognition from a sequence of images,
IVC(20), No. 3, March 2002, pp. 227-235.
WWW Link. 0202
BibRef

Luck, B.L., Carlson, K.D., Bovik, A.C., Richards-Kortum, R.R.,
An Image Model and Segmentation Algorithm for Reflectance Confocal Images of In Vivo Cervical Tissue,
IP(14), No. 9, September 2005, pp. 1265-1276.
IEEE DOI 0508
BibRef

Braumann, U.D., Kuska, J.P., Einenkel, J., Horn, L.C., Loffler, M., Hockel, M.,
Three-Dimensional Reconstruction and Quantification of Cervical Carcinoma Invasion Fronts From Histological Serial Sections,
MedImg(24), No. 10, October 2005, pp. 1286-1307.
IEEE DOI 0510
BibRef

Gavião, W.[Wilson], Scharcanski, J.[Jacob],
Evaluating the mid-secretory endometrium appearance using hysteroscopic digital video summarization,
IVC(25), No. 1, January 2007, pp. 70-77.
WWW Link. 0611
Medical image analysis; Video summarization; Hysteroscopies; Gynecology BibRef

Scharcanski, J., Gaviao, W.,
Hierarchical Summarization of Diagnostic Hysteroscopy Videos,
ICIP06(129-132).
IEEE DOI 0610
BibRef

Yang-Mao, S.F.[Shys-Fan], Chan, Y.K., Chu, Y.P.,
Edge Enhancement Nucleus and Cytoplast Contour Detector of Cervical Smear Images,
SMC-B(37), No. 2, April 2007, pp. 353-366.
IEEE DOI 0803
BibRef

Tsai, M.H.[Meng-Husiun], Chan, Y.K.[Yung-Kuan], Lin, Z.Z.[Zhe-Zheng], Yang-Mao, S.F.[Shys-Fan], Huang, P.C.[Po-Chi],
Nucleus and cytoplast contour detector of cervical smear image,
PRL(29), No. 9, 1 July 2008, pp. 1441-1453.
WWW Link. 0711
Cervical smear screening; Cervical cancer; Image segmentation; Salt and pepper noise; Gaussian noise; Contour detection BibRef

Lin, C.H.[Chuen-Horng], Chan, Y.K.[Yung-Kuan], Chen, C.C.[Chun-Chieh],
Detection and segmentation of cervical cell cytoplast and nucleus,
IJIST(19), No. 3, September 2009, pp. 260-270.
DOI Link 0909
BibRef

Staring, M., van der Heide, U.A., Klein, S., Viergever, M.A., Pluim, J.P.W.,
Registration of Cervical MRI Using Multifeature Mutual Information,
MedImg(28), No. 9, September 2009, pp. 1412-1421.
IEEE DOI 0909
BibRef

Langerak, T.R., van der Heide, U.A., Kotte, A.N.T.J., Viergever, M.A., van Vulpen, M., Pluim, J.P.W.,
Label Fusion in Atlas-Based Segmentation Using a Selective and Iterative Method for Performance Level Estimation (SIMPLE),
MedImg(29), No. 12, December 2010, pp. 2000-2008.
IEEE DOI 1101
BibRef

Langerak, T.R., van der Heide, U.A., Kotte, A.N.T.J., Berendsen, F.F., Pluim, J.P.W.,
Improving label fusion in multi-atlas based segmentation by locally combining atlas selection and performance estimation,
CVIU(130), No. 1, 2015, pp. 71-79.
Elsevier DOI 1411
Atlas-based segmentation BibRef

Greenspan, H., Gordon, S., Zimmerman, G., Lotenberg, S., Jeronimo, J.[Jose], Antani, S.[Sameer], Long, L.R.[L. Rodney],
Automatic Detection of Anatomical Landmarks in Uterine Cervix Images,
MedImg(28), No. 3, March 2009, pp. 454-468.
IEEE DOI 0903
BibRef

Rahman, M.M.[M. Mahmudur], Antani, S.K.[Sameer K.], Thoma, G.R.[George R.],
Biomedical Image Retrieval in a Fuzzy Feature Space with Affine Region Detection and Vector Quantization of a Scale-Invariant Descriptor,
ISVC10(III: 261-270).
Springer DOI 1011
BibRef

Xue, Z.Y.[Zhi-Yun], Long, L.R.[L. Rodney], Antani, S.K.[Sameer K.], Thoma, G.R.[George R.], Jeronimo, J.[Jose],
Cervicographic image retrieval by spatial similarity of lesions,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Alush, A.[Amir], Greenspan, H., Goldberger, J.[Jacob],
Automated and Interactive Lesion Detection and Segmentation in Uterine Cervix Images,
MedImg(29), No. 2, February 2010, pp. 488-501.
IEEE DOI 1002
BibRef

Gordon, S.[Shiri], Greenspan, H.[Hayit],
An agglomerative segmentation framework for non-convex regions within uterine cervix images,
IVC(28), No. 12, December 2010, pp. 1682-1701.
Elsevier DOI 1003
Medical image analysis; Image segmentation; Graph cuts; Cervical cancer; Cervicography images BibRef

Park, S.Y., Sargent, D., Lieberman, R., Gustafsson, U.,
Domain-Specific Image Analysis for Cervical Neoplasia Detection Based on Conditional Random Fields,
MedImg(30), No. 3, March 2011, pp. 867-878.
IEEE DOI 1103
BibRef

Li, K.[Kuan], Lu, Z.[Zhi], Liu, W.[Wenyin], Yin, J.P.[Jian-Ping],
Cytoplasm and nucleus segmentation in cervical smear images using Radiating GVF Snake,
PR(45), No. 4, April 2012, pp. 1255-1264.
Elsevier DOI 1112
Cervical cell; Boundary extraction; Radiating gradient vector flow; Active contour BibRef

Lu, C.[Chao], Chelikani, S., Jaffray, D.A., Milosevic, M.F., Staib, L.H., Duncan, J.S.,
Simultaneous Nonrigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy,
MedImg(31), No. 6, June 2012, pp. 1213-1227.
IEEE DOI 1206
BibRef

Gençtav, A.[Asli], Aksoy, S.[Selim], Önder, S.[Sevgen],
Unsupervised segmentation and classification of cervical cell images,
PR(45), No. 12, December 2012, pp. 4151-4168.
Elsevier DOI 1208
Pap smear test; Cell grading; Automatic thresholding; Hierarchical segmentation; Multi-scale segmentation; Hierarchical clustering; Ranking; Optimal leaf ordering BibRef

Steger, S., Bozoglu, N., Kuijper, A., Wesarg, S.,
Application of Radial Ray Based Segmentation to Cervical Lymph Nodes in CT Images,
MedImg(32), No. 5, May 2013, pp. 888-900.
IEEE DOI 1305
BibRef

Berendsen, F.F.[Floris F.], van der Heide, U.A.[Uulke A.], Langerak, T.R.[Thomas R.], Kotte, A.N.T.J.[Alexis N.T.J.], Pluim, J.P.W.[Josien P.W.],
Free-form image registration regularized by a statistical shape model: application to organ segmentation in cervical MR,
CVIU(117), No. 9, 2013, pp. 1119-1127.
Elsevier DOI 1307
Inter-subject BibRef

Hiary, H.[Hazem], Alomari, R.S.[Raja S.], Chaudhary, V.[Vipin],
Segmentation and localisation of whole slide images using unsupervised learning,
IET-PR(7), No. 5, 2013, pp. 464-471.
DOI Link 1310
BibRef

Hiary, H.[Hazem], Alomari, R.S.[Raja S.], Saadah, M.[Maha], Chaudhary, V.[Vipin],
Automated segmentation of stromal tissue in histology images using a voting Bayesian model,
SIViP(7), No. 6, November 2013, pp. 1229-1237.
Springer DOI 1310
BibRef

Torheim, T., Malinen, E., Kvaal, K., Lyng, H., Indahl, U.G., Andersen, E.K.F., Futsaether, C.M.,
Classification of Dynamic Contrast Enhanced MR Images of Cervical Cancers Using Texture Analysis and Support Vector Machines,
MedImg(33), No. 8, August 2014, pp. 1648-1656.
IEEE DOI 1408
Accuracy BibRef

Cengizler, C.[Caglar], Guven, M.[Mustafa], Avci, M.[Mutlu],
A fluid dynamics-based deformable model for segmentation of cervical cell images,
SIViP(8), No. S1, December 2014, pp. 21-32.
WWW Link. 1411
BibRef

Song, D.[Dezhao], Kim, E., Huang, X.L.[Xiao-Lei], Patruno, J., Munoz-Avila, H., Heflin, J., Long, L.R., Antani, S.,
Multimodal Entity Coreference for Cervical Dysplasia Diagnosis,
MedImg(34), No. 1, January 2015, pp. 229-245.
IEEE DOI 1502
biological organs BibRef

Lu, Z.[Zhi], Carneiro, G., Bradley, A.P.,
An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells,
IP(24), No. 4, April 2015, pp. 1261-1272.
IEEE DOI 1503
biomedical optical imaging BibRef

Lindblad, J.[Joakim], Bengtsson, E.[Ewert], Sladoje, N.[Nataša],
Microscopy Image Enhancement for Cost-Effective Cervical Cancer Screening,
SCIA15(440-451).
Springer DOI 1506
BibRef

Tan, M., Li, Z., Qiu, Y., McMeekin, S.D., Thai, T.C., Ding, K., Moore, K.N., Liu, H., Zheng, B.,
A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration,
MedImg(35), No. 1, January 2016, pp. 316-325.
IEEE DOI 1601
Cancer BibRef

Zhang, J.W.[Jian-Wei], Hu, Z.P.[Zhen-Peng], Han, G.Q.[Guo-Qiang], He, X.Z.[Xiao-Zhen],
Segmentation of overlapping cells in cervical smears based on spatial relationship and Overlapping Translucency Light Transmission Model,
PR(60), No. 1, 2016, pp. 286-295.
Elsevier DOI 1609
Cervical overlapping cell BibRef

Xu, T.[Tao], Zhang, H.[Han], Xin, C.[Cheng], Kim, E.[Edward], Long, L.R.[L. Rodney], Xue, Z.Y.[Zhi-Yun], Antani, S.[Sameer], Huang, X.L.[Xiao-Lei],
Multi-feature based benchmark for cervical dysplasia classification evaluation,
PR(63), No. 1, 2017, pp. 468-475.
Elsevier DOI 1612
Cervical cancer screening BibRef

Song, Y., Tan, E.L., Jiang, X., Cheng, J.Z., Ni, D., Chen, S., Lei, B., Wang, T.,
Accurate Cervical Cell Segmentation from Overlapping Clumps in Pap Smear Images,
MedImg(36), No. 1, January 2017, pp. 288-300.
IEEE DOI 1701
Cervical cancer BibRef

Cunningham, R.J., Harding, P.J., Loram, I.D.,
Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure,
MedImg(36), No. 2, February 2017, pp. 653-665.
IEEE DOI 1702
Image segmentation BibRef

Zhao, L.[Lili], Li, K.[Kuan], Yin, J.[Jianping], Liu, Q.[Qiang], Wang, S.[Siqi],
Complete three-phase detection framework for identifying abnormal cervical cells,
IET-IPR(11), No. 4, April 2017, pp. 258-265.
DOI Link 1704
BibRef


Fernandes, K.[Kelwin], Cardoso, J.S.[Jaime S.], Astrup, B.S.[Birgitte Schmidt],
Automated Detection and Categorization of Genital Injuries Using Digital Colposcopy,
IbPRIA17(251-258).
Springer DOI 1706
BibRef

Fernandes, K.[Kelwin], Cardoso, J.S.[Jaime S.], Fernandes, J.[Jessica],
Transfer Learning with Partial Observability Applied to Cervical Cancer Screening,
IbPRIA17(243-250).
Springer DOI 1706
BibRef

Neghina, M., Rasche, C., Ciuc, M., Sultana, A., Tiganesteanu, C.,
Automatic detection of cervical cells in Pap-smear images using polar transform and k-means segmentation,
IPTA16(1-6)
IEEE DOI 1703
cellular biophysics BibRef

Saha, R., Bajger, M., Lee, G.,
Spatial Shape Constrained Fuzzy C-Means (FCM) Clustering for Nucleus Segmentation in Pap Smear Images,
DICTA16(1-8)
IEEE DOI 1701
Cervical cancer BibRef

Ragothaman, S., Narasimhan, S., Basavaraj, M.G., Dewar, R.,
Unsupervised Segmentation of Cervical Cell Images Using Gaussian Mixture Model,
Microscopy16(1374-1379)
IEEE DOI 1612
BibRef

Lee, H.S.[Han-Sang], Kim, J.[Junmo],
Segmentation of Overlapping Cervical Cells in Microscopic Images with Superpixel Partitioning and Cell-Wise Contour Refinement,
Microscopy16(1367-1373)
IEEE DOI 1612
BibRef

Phoulady, H.A., Zhou, M., Goldgof, D.B., Hall, L.O., Mouton, P.R.,
Automatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling,
ICIP16(2658-2662)
IEEE DOI 1610
Adaptation models BibRef

Shahriar Sazzad, T.M., Armstrong, L.J., Tripathy, A.K.,
Type P63 Digitized Color Images Performs Better Identification than Other Stains for Ovarian Tissue Analysis,
AMDO16(44-54).
Springer DOI 1608
BibRef

Xu, T.[Tao], Xin, C.[Cheng], Long, L.R.[L. Rodney], Antani, S.[Sameer], Xue, Z.Y.[Zhi-Yun], Kim, E.[Edward], Huang, X.L.[Xiao-Lei],
A New Image Data Set and Benchmark for Cervical Dysplasia Classification Evaluation,
MLMI15(26-35).
Springer DOI 1511
BibRef

Fernandes, K.[Kelwin], Cardoso, J.S.[Jaime S.], Fernandes, J.[Jessica],
Temporal Segmentation of Digital Colposcopies,
IbPRIA15(262-271).
Springer DOI 1506
BibRef

Mehnert, A.[Andrew], Moshavegh, R.[Ramin], Sujathan, K., Malm, P.[Patrik], Bengtsson, E.[Ewert],
A Structural Texture Approach for Characterising Malignancy Associated Changes in Pap Smears Based on Mean-Shift and the Watershed Transform,
ICPR14(1189-1193)
IEEE DOI 1412
Bandwidth BibRef

Orozco-Monteagudo, M.[Maykel], Taboada-Crispi, A.[Alberto], Sahli, H.[Hichem],
Biologically Inspired Anomaly Detection in Pap-Smear Images,
CIARP13(II:17-24).
Springer DOI 1311
BibRef

Lorenzo-Ginori, J.V.[Juan Valentín], Curbelo-Jardines, W.[Wendelin], López-Cabrera, J.D.[José Daniel],
Cervical Cell Classification Using Features Related to Morphometry and Texture of Nuclei,
CIARP13(II:222-229).
Springer DOI 1311
BibRef

Chaudhury, B.[Baishali], Phoulady, H.A.[Hady Ahmady],
An Ensemble Algorithm Framework for Automated Stereology of Cervical Cancer,
CIAP13(I:823-832).
Springer DOI 1311
BibRef

Fan, J.P.[Jin-Ping], Wang, R.C.[Rui-Chun], Li, S.G.[Shi-Guo], Zhang, C.X.[Chun-Xiao],
Automated cervical cell image segmentation using level set based active contour model,
ICARCV12(877-882).
IEEE DOI 1304
BibRef

Plissiti, M.E.[Marina E.], Nikou, C.[Christophoros],
Cervical Cell Classification Based Exclusively on Nucleus Features,
ICIAR12(II: 483-490).
Springer DOI 1206
BibRef

Mehrotra, P.[Palak], Chakraborty, C.[Chandan], Ghoshdastidar, B.[Biswanath], Ghoshdastidar, S.[Sudarshan], Ghoshdastidar, K.[Kakoli],
Automated ovarian follicle recognition for Polycystic Ovary Syndrome,
ICIIP11(1-4).
IEEE DOI 1112
BibRef

Kale, A.[Asli], Aksoy, S.[Selim],
Segmentation of Cervical Cell Images,
ICPR10(2399-2402).
IEEE DOI 1008
BibRef

Wilhelm, M.[Matthew], Nutter, B.[Brian], Long, R.[Rodney], Antani, S.[Sameer],
Automated Detection of Human Papillomavirus: Via Analysis of Linear Array Images,
Southwest10(205-208).
IEEE DOI 1005
BibRef

Chen, T.[Terrence], Zhang, W.[Wei], Good, S.[Sara], Zhou, K.S.[Kevin S.], Comaniciu, D.[Dorin],
Automatic ovarian follicle quantification from 3D ultrasound data using global/local context with database guided segmentation,
ICCV09(795-802).
IEEE DOI 0909
BibRef

Malm, P.[Patrik], Brun, A.[Anders],
Closing Curves with Riemannian Dilation: Application to Segmentation in Automated Cervical Cancer Screening,
ISVC09(I: 337-346).
Springer DOI 0911
BibRef

Wang, W.[Wei], Huang, X.L.[Xiao-Lei],
Distance guided selection of the best base classifier in an ensemble with application to cervigram image segmentation,
MMBIA09(109-116).
IEEE DOI 0906
BibRef

Signolle, N.[Nicolas], Plancoulaine, B.[Benoît], Herlin, P.[Paulette], Revenu, M.[Marinette],
Texture-Based Multiscale Segmentation: Application to Stromal Compartment Characterization on Ovarian Carcinoma Virtual Slides,
ICISP08(173-182).
Springer DOI 0807
BibRef

Wang, Y.H.[Yin-Hai], Turner, R.[Richard], Crookes, D.[Danny], Diamond, J.[Jim], Hamilton, P.[Peter],
Investigation of Methodologies for the Segmentation of Squamous Epithelium from Cervical Histological Virtual Slides,
IMVIP07(83-90).
IEEE DOI 0709
BibRef

Acosta-Mesa, H.G.[Héctor-Gabriel], Cruz-Ramírez, N.[Nicandro], Hernández-Jiménez, R.[Rodolfo], García-López, D.A.[Daniel-Alejandro],
Modeling Aceto-White Temporal Patterns to Segment Colposcopic Images,
IbPRIA07(II: 548-555).
Springer DOI 0706
BibRef

Maldonado-Castillo, I.[Idalia], Eramian, M.G.[Mark G.], Pierson, R.A.[Roger A.], Singh, J.[Jaswant], Adams, G.P.[Gregg P.],
Classification of Bovine Reproductive Cycle Phase using Ultrasound-Detected Features,
CRV07(258-265).
IEEE DOI 0705
BibRef

Lawrence, M.J.[Maryruth J.], Eramian, M.G.[Mark G.], Pierson, R.A.[Roger A.], Neufeld, E.[Eric],
Computer Assisted Detection of Polycystic Ovary Morphology in Ultrasound Images,
CRV07(105-112).
IEEE DOI 0705
BibRef

Dvir, H.[Hila], Gordon, S.[Shiri], Greenspan, H.[Hayit],
Illumination Correction for Content Analysis in Uterine Cervix Images,
MMBIA06(95).
IEEE DOI 0609
BibRef

Li, W.J.[Wen-Jing], Poirson, A.[Allen],
Detection and Characterization of Abnormal Vascular Patterns in Automated Cervical Image Analysis,
ISVC06(II: 627-636).
Springer DOI 0611
BibRef

Srivastava, S., Rodriguez, J.J., Rouse, A.R., Brewer, M.A., Gmitro, A.F.,
Analysis of Confocal Microendoscope Images for Automatic Detection of Ovarian Cancer,
ICIP05(I: 1113-1116).
IEEE DOI 0512
BibRef

Raad, V.[Viara],
A New Vision Approach for Local Spectrum Features in Cervical Images via 2D Method of Geometric Restriction in Frequency Domain,
CVBIA05(125-134).
Springer DOI 0601
BibRef

Li, W.J.[Wen-Jing], Raad, V.[Viara], Gu, J.[Jia], Hansson, U.[Ulf], Hakansson, J.[Johan], Lange, H.[Holger], Ferris, D.[Daron],
Computer-Aided Diagnosis (CAD) for Cervical Cancer Screening and Diagnosis: A New System Design in Medical Image Processing,
CVBIA05(240-250).
Springer DOI 0601
BibRef

Luck, B.L., Bovik, A.C., Richards-Korium, R.R.,
Segmenting cervical epithelial nuclei from confocal images using gaussian markov random fields,
ICIP03(II: 1069-1072).
IEEE DOI 0312
BibRef

Balas, C., Themelis, G., Papadakis, A., Vasgiouraki, E., Argyros, A., Koumantakis, E., Tosca, A., Helidonis, E.,
A Novel Hyper-Spectral Imaging System: Application on in-vivo Detection and Grading of Cervical Precancers and of Pigmented Skin Lesions,
CVBVS01(xx-yy). 0110
BibRef

Ouadfel, S., Batouche, M., Meshoul, S.,
A Fuzzy-Connectionist System for Diagnosing Cervical Cancer from Cell Images,
ICPR98(CVP1). 9808
Not online. BibRef

Schulerud, H.[Helene], Kristensen, G.K., Vlatkovic, L., Albregtsen, F., Liestol, K., and Danielsen, H.E.,
Prognosis of Cervical Cancer Using Image Analysis of Cell Nuclei,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Mackin, Jr., R.W., Roysam, B., Turner, J.N.,
Adaptive 3-D segmentation algorithms for microscope images using local in-focus, and contrast features: application to Pap smears,
ICIP95(III: 160-163).
IEEE DOI 9510
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Medical Applications -- Skin Cancer, Melanoma, Skin Lesions .


Last update:Sep 25, 2017 at 16:36:46