BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

158 related articles for article (PubMed ID: 33600310)

  • 21. A pap-smear analysis tool (PAT) for detection of cervical cancer from pap-smear images.
    William W; Ware A; Basaza-Ejiri AH; Obungoloch J
    Biomed Eng Online; 2019 Feb; 18(1):16. PubMed ID: 30755214
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Segmentation of acetowhite region in uterine cervical image based on deep learning.
    Liu J; Liang T; Peng Y; Peng G; Sun L; Li L; Dong H
    Technol Health Care; 2022; 30(2):469-482. PubMed ID: 34180439
    [TBL] [Abstract][Full Text] [Related]  

  • 23. NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images.
    Lal S; Das D; Alabhya K; Kanfade A; Kumar A; Kini J
    Comput Biol Med; 2021 Jan; 128():104075. PubMed ID: 33190012
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Weakly-supervised convolutional neural networks of renal tumor segmentation in abdominal CTA images.
    Yang G; Wang C; Yang J; Chen Y; Tang L; Shao P; Dillenseger JL; Shu H; Luo L
    BMC Med Imaging; 2020 Apr; 20(1):37. PubMed ID: 32293303
    [TBL] [Abstract][Full Text] [Related]  

  • 25. BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis.
    Zhang E; Seiler S; Chen M; Lu W; Gu X
    Phys Med Biol; 2020 Jun; 65(12):125005. PubMed ID: 32155605
    [TBL] [Abstract][Full Text] [Related]  

  • 26. CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.
    Wang H; Gu H; Qin P; Wang J
    PLoS One; 2020; 15(11):e0242013. PubMed ID: 33166371
    [TBL] [Abstract][Full Text] [Related]  

  • 27. HVS-Unsup: Unsupervised cervical cell instance segmentation method based on human visual simulation.
    Yang X; Ding B; Qin J; Guo L; Zhao J; He Y
    Comput Biol Med; 2024 Mar; 171():108147. PubMed ID: 38387385
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Automated quantification of renal interstitial fibrosis for computer-aided diagnosis: A comprehensive tissue structure segmentation method.
    Tey WK; Kuang YC; Ooi MP; Khoo JJ
    Comput Methods Programs Biomed; 2018 Mar; 155():109-120. PubMed ID: 29512490
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Computer-aided diagnosis tool for cervical cancer screening with weakly supervised localization and detection of abnormalities using adaptable and explainable classifier.
    Pirovano A; Almeida LG; Ladjal S; Bloch I; Berlemont S
    Med Image Anal; 2021 Oct; 73():102167. PubMed ID: 34333217
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A computer-aided diagnosis system for differentiation and delineation of malignant regions on whole-slide prostate histopathology image using spatial statistics and multidimensional DenseNet.
    Chen CM; Huang YS; Fang PW; Liang CW; Chang RF
    Med Phys; 2020 Mar; 47(3):1021-1033. PubMed ID: 31834623
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Generating region proposals for histopathological whole slide image retrieval.
    Ma Y; Jiang Z; Zhang H; Xie F; Zheng Y; Shi H; Zhao Y; Shi J
    Comput Methods Programs Biomed; 2018 Jun; 159():1-10. PubMed ID: 29650303
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.
    P B S; Faruqi F; K S H; Kudva R
    Asian Pac J Cancer Prev; 2019 Nov; 20(11):3447-3456. PubMed ID: 31759371
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Breast cancer histopathology image classification through assembling multiple compact CNNs.
    Zhu C; Song F; Wang Y; Dong H; Guo Y; Liu J
    BMC Med Inform Decis Mak; 2019 Oct; 19(1):198. PubMed ID: 31640686
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Weakly supervised histopathology cancer image segmentation and classification.
    Xu Y; Zhu JY; Chang EI; Lai M; Tu Z
    Med Image Anal; 2014 Apr; 18(3):591-604. PubMed ID: 24637156
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Development of Algorithms for Automated Detection of Cervical Pre-Cancers With a Low-Cost, Point-of-Care, Pocket Colposcope.
    Asiedu MN; Simhal A; Chaudhary U; Mueller JL; Lam CT; Schmitt JW; Venegas G; Sapiro G; Ramanujam N
    IEEE Trans Biomed Eng; 2019 Aug; 66(8):2306-2318. PubMed ID: 30575526
    [TBL] [Abstract][Full Text] [Related]  

  • 36. CNSeg: A dataset for cervical nuclear segmentation.
    Zhao J; He YJ; Zhou SH; Qin J; Xie YN
    Comput Methods Programs Biomed; 2023 Nov; 241():107732. PubMed ID: 37544166
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Ensemble U-net-based method for fully automated detection and segmentation of renal masses on computed tomography images.
    Fatemeh Z; Nicola S; Satheesh K; Eranga U
    Med Phys; 2020 Sep; 47(9):4032-4044. PubMed ID: 32329074
    [TBL] [Abstract][Full Text] [Related]  

  • 38. BS-80K: The first large open-access dataset of bone scan images.
    Huang Z; Pu X; Tang G; Ping M; Jiang G; Wang M; Wei X; Ren Y
    Comput Biol Med; 2022 Dec; 151(Pt A):106221. PubMed ID: 36334360
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Automatic segmentation of cervical region in colposcopic images using K-means.
    Bai B; Liu PZ; Du YZ; Luo YM
    Australas Phys Eng Sci Med; 2018 Dec; 41(4):1077-1085. PubMed ID: 30215221
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.
    Al-Antari MA; Al-Masni MA; Choi MT; Han SM; Kim TS
    Int J Med Inform; 2018 Sep; 117():44-54. PubMed ID: 30032964
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.