Theres quite a few medical imaging datasets out there. Heres a list with some:

• Current state of the art of most used computer vision datasets: Who is the best at X? http://rodrigob.github.io/are_we_there_yet/build/
• Medical Decathlon Competition Datasets: https://drive.google.com/drive/folders/1HqEgzS8BV2c7xYNrZdEAnrHk7osJJ--2
• Grand Challenges in Medical Image Analysis http://www.grand-challenge.org/index.php/Main_Page
• Multimodal databases
  • Center for Invivo Microscopy (CIVM), Embrionic and Neonatal Mouse (H&E, MR) http://www.civm.duhs.duke.edu/devatlas/ http://www.civm.duhs.duke.edu/devatlas/UserGuide.pdf
  • LONI image data archive https://ida.loni.usc.edu/services/Menu/IdaData.jsp?project=
• Radiology (Ultrasound, Mammographs, X-Ray, CT, MRI, fMRI, etc.)
  • COllaborative Informatics and Neuroimaging Suite (COINS) https://portal.mrn.org/micis/index.php?subsite=dx
  • The Cancer Imaging Archive (TCIA) http://www.cancerimagingarchive.net/ (Collections)
  • Alzheimer’s Disease Neuroimaging Initiative (ADNI) http://adni.loni.ucla.edu/
  • The Open Access Series of Imaging Studies (OASIS) http://www.oasis-brains.org/
  • Breast Cancer Digital Repository http://bcdr.inegi.up.pt/
  • DDSM: Digital Database for Screening Mammography http://marathon.csee.usf.edu/Mammography/Database.html
  • The Mammographic Image Analysis Society (MIAS) mini-database http://peipa.essex.ac.uk/info/mias.html
  • Mammography Image Databases 100 or more images of mammograms with ground truth. Additional images available by request, and links to several other mammography databases are provided http://marathon.csee.usf.edu/Mammography/Database.html
  • NLM HyperDoc Visible Human Project color, CAT and MRI image samples - over 30 images http://www.nlm.nih.gov/research/visible/visible_human.html
• Histology and Histopathology (H&E, IHQ, ...)
  • The International Society for Digital Imaging of the Skin (ISDIS): https://isdis.net/home
  • The Histology Image Dataset (histologyDS) http://www.informed.unal.edu.co/histologyDS
  • The Cancer Genome Atlas (TCGA) http://cancergenome.nih.gov/ https://tcga-data.nci.nih.gov/tcga/
  • International Cancer Genome Consortium http://icgc.org, (Data portal) http://dcc.icgc.org/
  • Stanford Tissue Microarray Database (TMA) http://tma.im
  • MITOS dataset http://ipal.cnrs.fr/ICPR2012/
  • Cancer Image Database (caIMAGE) http://cancerim ages.nci.nih.gov/caIMAGE/
  • DPA’s Whole Slide Imaging Repository https://digitalpathologyassociation.org/whole-slide-imaging-repository
  • Atlas of breast Histology http://www.webmicroscope.net/atlases/breast/brcatlas_start.asp
  • ITK Analysis of Large Histology Datasets http://www.na-mic.org/Wiki/index.php/ITK_Analysis_of_Large_Histology_Datasets
  • Histology Photo Album http://www.histology-world.com/photoalbum/thumbnails.php?album=52
  • Slide Library of Virtual pathology, University of Leeds http://www.virtualpathology.leeds.ac.uk/
  • Tissue Acquisition and Banking Services (TABS) of the NYU Experimental Pathology Core Facilities http://pathology.med.nyu.edu/research/core-laboratories/tissue-banking
  • Aperio Images http://images2.aperio.com/
  • HAPS Histology Image Database http://hapshistology.wikifoundry.com/
• Microscopy (Cell, Cytology, Biology, Protein, Molecular, Fluorescence, etc.)
  • BDGP images from the FlyExpress database www.flyexpress.net
  • The UCSB Bio-Segmentation Benchmark dataset http://www.bioimage.ucsb.edu/research/biosegmentation
  • Pap Smear database http://labs.fme.aegean.gr/decision/downloads
  • BIICBU Biological Image Repository http://ome.grc.nia.nih.gov/iicbu2008/
  • RNAi dataset http://ome.grc.nia.nih.gov/iicbu2008/rnai/index.html
  • Chinese Hamster Ovary cells (CHO) dataset http://ome.grc.nia.nih.gov/iicbu2008/hela/index.html#cho
  • Locate Endogenus mouse sub-cellular organelles (END) databaset http://locate.imb.uq.edu.au/
  • 2D HeLa dataset (HeLa) datgaset http://ome.grc.nia.nih.gov/iicbu2008/hela/index.html
  • Allen Brain Atlas http://www.brain-map.org/
  • 1000 Functional Connectomes Project http://fcon_1000.projects.nitrc.org/
  • The Cell Centered Database (CCDB) http://ccdb.ucsd.edu/index.shtm
  • The Encyclopedia of DNA Elements (ENCODE) http://genome.ucsc.edu/ENCODE/ http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001046
  • The Human Protein Atlas: http://www.proteinatlas.org/
  • DRIVE: Digital Retinal Images for Vessel Extraction http://www.isi.uu.nl/Research/Databases/DRIVE/ (Ground truth)
  • El Salvador Atlas of Gastrointestinal VideoEndoscopy Images and Videos of his-res of studies taken from Gastrointestinal Video endoscopy http://www.gastrointestinalatlas.com/
• Computer Vision
  • The Street View House Numbers (SVHN) Dataset http://ufldl.stanford.edu/housenumbers/
  • The PASCAL Object Recognition Database Collection http://pascallin.ecs.soton.ac.uk/challenges/VOC/databases.html
  • ImageNet http://www.image-net.org/
  • Motion-based Segmentation and Recognition Dataset http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/
  • The AR Face Database http://www2.ece.ohio-state.edu/~aleix/ARdatabase.html
  • The Extended M2VTS Database (XM2VTSDB) http://www.ee.surrey.ac.uk/CVSSP/xm2vtsdb/
  • CBCL Face Database http://cbcl.mit.edu/software-datasets/FaceData2.html
  • STL-10 http://www.stanford.edu/~acoates//stl10/
  • The USC-SIPI Image Database is a collection of digitized images. (Textures, Aerials, Miscellaneous, Sequences) http://sipi.usc.edu/DATABASE/database.php
• Databases you can use for bechmarking 
  • http://peipa.essex.ac.uk/benchmark/databases/
  • http://mulan.sourceforge.net/datasets-mlc.html
  • https://archive.ics.uci.edu/ml/datasets.html
  • http://www.dmoz.org/Computers/Artificial_Intelligence/Machine_Learning/Datasets/
  • Benchmark Data Sets for Highly Imbalanced Binary Classification http://www.cs.gsu.edu/~zding/research/benchmark-data.php
• Datasets reporting formats for pathologists http://www.rcpath.org/publications-media/publications/datasets
• DermNet - Skin disease atlas (23 image classes and 23,000 images): http://www.dermnet.com/

@ Marco Antônio Vieira Macedo Grinet thank you sir

I recommend using PDDCA database:

http://www.imagenglab.com/newsite/pddca/

It contains manual segmentation of left and right parotid glands, brainstem, optic chiasm, optic nerves (both left and right), mandible, submandibular glands (both left and right) and manual identification of bony landmarks.

Thanks Fatemeh Abdolali