Datasets:

FIVE-MGI
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SiDoLa-NS-Macro-mCB

text stringlengths 8 14.8k
Agranular Insular Area
Anterior Area
Arcuate Hypothalamic Nucleus
Auditory Areas
Basolateral Amygdalar Nucleus
Basomedial Amygdalar Nucleus
Caudoputamen
Cortical Amygdalar Area Anterior
Dentate Gyrus Granule-Cell Layer
Dorsomedial Nucleus Hypothalamus
Ectorhinal Area
Endopiriform Nucleus
Fibers Optic Radiation
Fibers Stria Terminalis
Hippocampal Region
Hypothalamus
Lateral Amygdalar Nucleus
Lateral Hypothalamic Area
Pallidum
Piriform Area
Piriform-Amygdalar Area
Retrosplenial Area
Somatosensory Area Of Isocortex
Striatum-Like Amygdalar Nuclei
Temporal Association Areas
Thalamus Large
Thalamus Polymodal
Ventral Group Of The Dorsal Thalamus
Ventromedial Hypothalamic Nucleus
Visceral Area
0 0.24489860236644745 0.5507453978061676 0.24404825270175934 0.5506277084350586 0.2420174777507782 0.5503459274768829 0.2395884394645691 0.5500101149082184 0.2375488132238388 0.5497282147407532 0.23669257760047913 0.5496113300323486 0.2361726462841034 0.5498355031013489 0.23493149876594543 0.5503714084625244 0.23344755...
1 0.750260055065155 0.18109476566314697 0.7512743473052979 0.1759399175643921 0.7525227069854736 0.16932731866836548 0.7516101598739624 0.16806453466415405 0.7494862079620361 0.1660522222518921 0.7494668960571289 0.16382944583892822 0.7507808804512024 0.15628844499588013 0.75100177526474 0.1535046100616455 0.7489564418...
2 0.825714647769928 0.7072605192661285 0.8255980610847473 0.7073335945606232 0.8252699375152588 0.707536369562149 0.8247632384300232 0.7078514099121094 0.8241099119186401 0.7082570493221283 0.8233429789543152 0.7087324857711792 0.8224947452545166 0.7092591822147369 0.8215981125831604 0.7098162174224854 0.82068502902984...
3 0.14038214087486267 0.2835114598274231 0.13872584700584412 0.2842950224876404 0.13616642355918884 0.28550267219543457 0.1356526017189026 0.2860236167907715 0.13552458584308624 0.28754323720932007 0.135442852973938 0.28852587938308716 0.1337890923023224 0.2893017530441284 0.13123327493667603 0.290497362613678 0.130721...
4 0.2969436049461365 0.6368955671787262 0.29642489552497864 0.6373082101345062 0.29496389627456665 0.6384679973125458 0.29270094633102417 0.6402663886547089 0.289776474237442 0.6425904929637909 0.2863316237926483 0.6453331410884857 0.28250980377197266 0.6483827829360962 0.278455913066864 0.6516262292861938 0.2743180990...
5 0.35430845618247986 0.7185570299625397 0.3515869379043579 0.7197626829147339 0.3450964689254761 0.7226499915122986 0.33735018968582153 0.7261240780353546 0.33086350560188293 0.7290601134300232 0.32814478874206543 0.7302978336811066 0.3277055323123932 0.7302499115467072 0.3266584575176239 0.7301334142684937 0.32540896...
6 0.40836381912231445 0.35724425315856934 0.40214988589286804 0.35671496391296387 0.39700978994369507 0.3563110828399658 0.39429542422294617 0.3580614924430847 0.3924303650856018 0.35899412631988525 0.3872235417366028 0.3585243225097656 0.3835090100765228 0.35947829484939575 0.3714010417461395 0.3672151565551758 0.3678...
7 0.3919208347797394 0.814673513174057 0.38918742537498474 0.8144036680459976 0.3826630711555481 0.8137546628713608 0.3748651146888733 0.8129743486642838 0.3683239817619324 0.8123157024383545 0.36557909846305847 0.8120385259389877 0.36456847190856934 0.8125599771738052 0.36216026544570923 0.8138010501861572 0.359288334...
8 0.6311816573143005 0.32273679971694946 0.6325549483299255 0.3242919445037842 0.6343267560005188 0.3262920379638672 0.6379671692848206 0.32664555311203003 0.6457395553588867 0.3271961808204651 0.6478694677352905 0.32681041955947876 0.6511270403862 0.3248800039291382 0.653023898601532 0.32427000999450684 0.660529553890...
9 0.8091572523117065 0.7173648774623871 0.8089708089828491 0.7173729240894318 0.8084843158721924 0.717391848564148 0.8078067898750305 0.7174185514450073 0.8070470094680786 0.7174482047557831 0.8063143491744995 0.717477947473526 0.805717945098877 0.7175013422966003 0.8053672909736633 0.7175138890743256 0.805278658866882...
10 0.14990806579589844 0.5065114796161652 0.14749738574028015 0.5062106847763062 0.14118781685829163 0.5054306983947754 0.13236142694950104 0.5043620765209198 0.12241807579994202 0.5031894445419312 0.1127852275967598 0.5020823776721954 0.10491824895143509 0.5012009739875793 0.10028328746557236 0.5006910562515259 0.0995...
11 0.21075180172920227 0.6867488026618958 0.21020494401454926 0.6870255768299103 0.2089018076658249 0.6876867711544037 0.20734763145446777 0.6884782910346985 0.20604638755321503 0.6891439259052277 0.2055007964372635 0.6894238591194153 0.20509132742881775 0.6893984079360962 0.2041151225566864 0.6893381774425507 0.202950...
12 0.9050444960594177 0.24542462825775146 0.8675643801689148 0.21519547700881958 0.832909345626831 0.1838744878768921 0.823696494102478 0.17902648448944092 0.8088651895523071 0.17903155088424683 0.7903305888175964 0.18158018589019775 0.7745463848114014 0.18551123142242432 0.7314090132713318 0.18601006269454956 0.703435...
13 0.541420578956604 0.4110199809074402 0.540074348449707 0.41088348627090454 0.5372044444084167 0.410591185092926 0.534557580947876 0.41032135486602783 0.5336533784866333 0.41031140089035034 0.5315342545509338 0.41168564558029175 0.5282086133956909 0.41384196281433105 0.5256261825561523 0.41551798582077026 0.525029301...
14 0.9290772676467896 0.3018619418144226 0.926948606967926 0.3017274737358093 0.9248166084289551 0.30159205198287964 0.9223297834396362 0.30307435989379883 0.919837474822998 0.3045564889907837 0.9112509489059448 0.3040049076080322 0.9026168584823608 0.3034402132034302 0.8916984796524048 0.2928315997123718 0.88065510988...
15 0.8236325979232788 0.6962878704071045 0.8259781002998352 0.6945100128650665 0.8296069502830505 0.6917616426944733 0.8299819231033325 0.6909779608249664 0.8283103108406067 0.6896234452724457 0.827226996421814 0.6887491941452026 0.8258698582649231 0.6888110637664795 0.8237708210945129 0.6889069676399231 0.823047876358...
16 0.2602250576019287 0.5557249188423157 0.25917431712150574 0.5588019490242004 0.25656214356422424 0.56614550948143 0.25325751304626465 0.5749189257621765 0.25034353137016296 0.582280308008194 0.2490849643945694 0.5853720009326935 0.24938662350177765 0.5857066214084625 0.2501041889190674 0.5865029692649841 0.250958323...
17 0.5389074683189392 0.6121402084827423 0.5370411276817322 0.6195032596588135 0.5395244359970093 0.6224485337734222 0.5397519469261169 0.6246442198753357 0.5361151099205017 0.6262698471546173 0.5300059914588928 0.6275982856750488 0.5262382626533508 0.6293899714946747 0.5255433917045593 0.6318447589874268 0.52856254577...
18 0.3676423132419586 0.5280851721763611 0.36693650484085083 0.5317698419094086 0.36528676748275757 0.5396211445331573 0.36358585953712463 0.5468623042106628 0.3630802631378174 0.5490769743919373 0.3638346493244171 0.5498590767383575 0.3650219440460205 0.5510907769203186 0.3659467101097107 0.5520514249801636 0.36602818...
19 0.1404752880334854 0.6005978584289551 0.13708463311195374 0.6023090183734894 0.13480934500694275 0.6032136380672455 0.13149721920490265 0.602981835603714 0.12922391295433044 0.6038966774940491 0.12584345042705536 0.6056469082832336 0.12313307821750641 0.6054706573486328 0.12057614326477051 0.6059444844722748 0.11234...
20 0.22454631328582764 0.8092772364616394 0.22431378066539764 0.8094133138656616 0.22370722889900208 0.8097676336765289 0.222863107919693 0.810261532664299 0.22191785275936127 0.8108153641223907 0.22100713849067688 0.8113502860069275 0.220266655087471 0.8117856383323669 0.21983160078525543 0.8120419383049011 0.21976414...
21 0.7450892329216003 0.07221049070358276 0.7450498342514038 0.07269233465194702 0.7449654936790466 0.07372194528579712 0.7448869943618774 0.07467442750930786 0.7449093461036682 0.07499963045120239 0.7458037734031677 0.07574981451034546 0.7472147345542908 0.07693278789520264 0.7483160495758057 0.07785683870315552 0.748...

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SiDoLa-NS-Macro-mCB

https://sidolans01.mgifive.org/

Dataset Summary

This dataset contains high-resolution microscopy images of central nervous system (CNS) coronal sections, together with their corresponding labels for training segmentation and detection models. The dataset is primarily intended for training and benchmarking deep learning pipelines (e.g., YOLO, SAHI, SAM-based workflows).

In addition to the raw images and labels, some dataset folders also contain: