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Search results for: FEED PER TOOTH
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GIST - Male, 82 - Tissue image [8160730027017261]
Open Research DataThis is the histopathological image of STOMACH tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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GIST - Female, 21 - Tissue image [8100730018737031]
Open Research DataThis is the histopathological image of SMALL INTESTINE tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Infiltrating lobular carcinoma, NOS - Female, 90 - Tissue image [8160730027003591]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Invasive breast carcinoma of no special type - Female, 63 - Tissue image [4190730010777601]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Lobular carcinoma, NOS - Female, 54 - Tissue image [10100730045402001]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Invasive breast carcinoma of no special type - Female, 59 - Tissue image [5030730005222251]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Neuroendocrine tumor, grade 1 - Female, 51 - Tissue image [8160730027004041]
Open Research DataThis is the histopathological image of COLON tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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GIST - Male, 81 - Tissue image [8170729597199171]
Open Research DataThis is the histopathological image of STOMACH tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Mucinous carcinoma - Female, 65 - Tissue image [8020729577647921]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Gastrointestinal stromal tumor - Female, 60 - Tissue image [8100730018732401]
Open Research DataThis is the histopathological image of STOMACH tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Metaplastic carcinoma, NOS - Female, 61 - Tissue image [8020729577643811]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Lobular carcinoma, noninfiltrating - Female, 71 - Tissue image [8160730027006871]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Infiltrating lobular carcinoma, NOS - Female, 90 - Tissue image [8160730027005121]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Neuroendocrine tumor, grade 1 - Female, 51 - Tissue image [816073002700151]
Open Research DataThis is the histopathological image of COLON tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Nodular melanoma - Female, 79 - Tissue image [9190729564907841]
Open Research DataThis is the histopathological image of SKIN tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adenocarcinoma, NOS - Female, 84 - Tissue image [2270630026324051]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Lobular carcinoma, NOS - Female, 54 - Tissue image [10100730045407371]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Neuroendocrine tumor, grade 1 - Female, 51 - Tissue image [8160730027001751]
Open Research DataThis is the histopathological image of COLON tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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GIST - Female, 21 - Tissue image [8100730018731481]
Open Research DataThis is the histopathological image of SMALL INTESTINE tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Invasive breast carcinoma of no special type - Female, 65 - Tissue image [7130729588544711]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Invasive breast carcinoma of no special type - Female, 35 - Tissue image [8020729577642011]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Infiltrating lobular carcinoma, NOS - Female, 60 - Tissue image [8160730027007451]
Open Research DataThis is the histopathological image of LYMPH NODES tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Invasive breast carcinoma of no special type - Male, 79 - Tissue image [4190730010785461]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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GIST - Female, 78 - Tissue image [815073000521171]
Open Research DataThis is the histopathological image of STOMACH tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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GIST - Female, 78 - Tissue image [8150730005218811]
Open Research DataThis is the histopathological image of STOMACH tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Lobular carcinoma, NOS - Female, 54 - Tissue image [1010073004540291]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adenocarcinoma, NOS - Female, 84 - Tissue image [2270630026327061]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Invasive breast carcinoma of no special type - Female, 42 - Tissue image [5040730020279961]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Lobular carcinoma, NOS - Female, 76 - Tissue image [3200630011573041]
Open Research DataThis is the histopathological image of BREAST tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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GIST - Male, 81 - Tissue image [8170729597194001]
Open Research DataThis is the histopathological image of STOMACH tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Pedestrian accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Pedestrians. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Young drivers accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: young driver offender. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Motorcycle and moped accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: motorcyclists and mopeds. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Head-on accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: head-on. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Side-impact accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Side-impact. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Run off road accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Run off road. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Elderly people accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: elderly people (65+) - drivers, passengers and . vulnerable road user. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Cyclist accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Cyclists. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Night accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, time of accidents: Night. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Excessive speed accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, cause of accidents: Excessive speed accidents. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Child accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: children - drivers, passengers and . vulnerable road user.. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Alcohol and drug accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Offenders under influence of alcohol or drug - driver or pedestrian. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Dataset for a research study on scientific productivity of Polish technical universities (Silesian University Of Technology 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.The raw data was retrieved in June 2021 by the SciVal benchmarking tool in xlsx format and will be used to create the research profiles of the universities and underlying data of journals articles.The most common definition of research productivity...
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Dataset for a research study on scientific productivity of Polish technical universities (Gdańsk Tech 2016-2020)
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities. The raw data was retrieved in June 2021 by the SciVal benchmarking tool in xlsx format and will be used to create the research profiles of the universities and underlying data of journals articles. The most common definition of research...
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Dataset for a research study on scientific productivity of Polish technical universities (Poznań University of Technology 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.
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Dataset for a research study on scientific productivity of Polish technical universities (Białystok University of Technology 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.
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Dataset for a research study on scientific productivity of Polish technical universities (Opole University of Technology 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.
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Dataset for a research study on scientific productivity of Polish technical universities (Lublin University of Technology 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.
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Dataset for a research study on scientific productivity of Polish technical universities (University of Bielsko-Biała ATH 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.
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Dataset for a research study on scientific productivity of Polish technical universities (Warsaw University of Technology 2016-2020).
Open Research DataThis dataset was created for the purpose of research on scientific productivity at Polish technical universities.