Datasets:

FIVE-MGI
/

SiDoLa-NS-Macro-mSC

text stringlengths 22 6.17k
Adductor motorneurons of lamina Lamina Lamina 8-9
Central Canal,Central Region,Lamina 7
Dorsal corticospinal tract,Dorsal Central Region,Dorsal Medial Region
Dorsal nucleus (Clarke)_5Sp,Dorsal Central Region,Dorsal Medial Region
Rubrospinal tract,Dorsal Lateral Region,Lateral Region
Dorsolateral fasciculus (Lissauer),Dorsal Central Region,Dorsal Medial Region
Lamina Lamina Lamina 7
Lamina Lamina Lamina 1-3
Lamina 2 Inner part,Lamina Lamina 1-3
Lamina 2 Outer part,Lamina Lamina 1-3
Lamina Lamina Lamina 1-3
Lamina Lamina Lamina 4-6
Lamina 5 Lateral part,Lamina Lamina 4-6
Lamina 5 Medial part,Lamina Lamina 4-6
Lamina 6 Lateral part,Lamina Lamina 4-6
Lamina 6 Medial part,Lamina Lamina 4-6
Lamina Lamina Lamina 7
Lamina Lamina Lamina 8-9
Lamina Lamina Lamina 8-9
Lateral cervical nucleus,Central Region,Dorsal Central Region
Ventral funiculus,Ventral funiculus,Ventral Funiculus
Lateral funiculus,Lateral funiculus,Lateral Region
Phrenic motoneurons of lamina Lamina Lamina 8-9
Postsynaptic dorsal column pathway,Lamina Lamina 8-9
Lateral spinal nucleus,Dorsal Lateral Region,Lateral Region
Dorsal corticospinal tract,Dorsal Central Region,Dorsal Medial Region
0 0.6740742325782776 0.9841152746230364 0.6724347472190857 0.9835917670279741 0.6681559085845947 0.9822255242615938 0.6621968746185303 0.9803227540105581 0.6555169820785522 0.9781898912042379 0.6490762233734131 0.9761332720518112 0.6438349485397339 0.9744597598910332 0.6407539248466492 0.9734759796410799 0.640231192111...
1 0.7155007719993591 0.8951263129711151 0.7155098915100098 0.8951988741755486 0.7155359387397766 0.8954064920544624 0.7155771255493164 0.8957342877984047 0.7156314253807068 0.8961671516299248 0.7156971096992493 0.8966901749372482 0.7157722115516663 0.8972883746027946 0.715854823589325 0.8979467153549194 0.7159431576728...
2 0.612546980381012 0.5312346816062927 0.6128164529800415 0.5335195064544678 0.6130860447883606 0.5358056724071503 0.6153489947319031 0.5387387871742249 0.6176132559776306 0.541673481464386 0.6178845763206482 0.5439641773700714 0.6181560754776001 0.5462561547756195 0.6204230785369873 0.5491956472396851 0.62269139289855...
3 0.6216529011726379 0.7421202659606934 0.6218493580818176 0.7438155114650726 0.6222691535949707 0.7474375367164612 0.6226574182510376 0.7507875114679337 0.6227290630340576 0.7518396377563477 0.6218559741973877 0.7527085095643997 0.620478630065918 0.7540792524814606 0.6194031238555908 0.7551496028900146 0.6194574832916...
4 0.24612975120544434 0.663578063249588 0.2474256008863449 0.6639944016933441 0.25051575899124146 0.6649871468544006 0.254203736782074 0.6661719381809235 0.2572934329509735 0.667164534330368 0.2585890591144562 0.6675807535648346 0.2590560019016266 0.6682219207286835 0.26016974449157715 0.6697511672973633 0.261499464511...
5 0.30160847306251526 0.5694758892059326 0.32075345516204834 0.589605301618576 0.3256323039531708 0.5928010046482086 0.3269411027431488 0.5916047096252441 0.32623401284217834 0.5879222750663757 0.32223594188690186 0.5825215578079224 0.3215709924697876 0.5740968883037567 0.3186088502407074 0.5692261755466461 0.316654652...
6 0.5466662049293518 0.8554231971502304 0.5467108488082886 0.8558491617441177 0.5468319058418274 0.857005700469017 0.5470104217529297 0.8587106764316559 0.5472273230552673 0.8607819229364395 0.5474634766578674 0.8630372285842896 0.5476997494697571 0.8652937710285187 0.5479170083999634 0.867368534207344 0.54809600114822...
7 0.3245762586593628 0.5817968845367432 0.32904142141342163 0.587853729724884 0.32984378933906555 0.5972743332386017 0.33401116728782654 0.598746120929718 0.3385609984397888 0.6046876013278961 0.34212613105773926 0.6054950952529907 0.33794018626213074 0.599404901266098 0.3369814455509186 0.5943422019481659 0.3329955637...
8 0.3446231484413147 0.5836789608001709 0.34903666377067566 0.5896244645118713 0.34946298599243164 0.594183623790741 0.35349446535110474 0.5998202562332153 0.3542834520339966 0.6043431162834167 0.361001193523407 0.6141361594200134 0.3686399757862091 0.618987500667572 0.37130218744277954 0.6173102259635925 0.36505514383...
9 0.6258245706558228 0.6110022068023682 0.6212512254714966 0.6050411760807037 0.6172295808792114 0.6037414968013763 0.6126635074615479 0.5977877676486969 0.608643651008606 0.5964884757995605 0.5995311737060547 0.5846022069454193 0.5914987325668335 0.5820052027702332 0.5869544148445129 0.576073169708252 0.58293974399566...
10 0.3553045690059662 0.5688584446907043 0.35675427317619324 0.5862345993518829 0.360186368227005 0.59208944439888 0.3615453541278839 0.5960077345371246 0.3652312755584717 0.6030600965023041 0.37524425983428955 0.6168481409549713 0.375619500875473 0.6212359666824341 0.37941157817840576 0.6224575936794281 0.382444947957...
11 0.3955910801887512 0.5773064494132996 0.39642202854156494 0.5866802334785461 0.392764687538147 0.5900619328022003 0.39442482590675354 0.6088999807834625 0.398927241563797 0.6149410307407379 0.39934656023979187 0.6196716129779816 0.40385720133781433 0.6257261037826538 0.41203773021698 0.6283619105815887 0.41655790805...
12 0.5447733998298645 0.6527876853942871 0.541513979434967 0.651736855506897 0.5370318293571472 0.6502918004989624 0.5356490015983582 0.6488580405712128 0.5328681468963623 0.6451791822910309 0.5314645767211914 0.6439251005649567 0.526796281337738 0.642419844865799 0.5239180326461792 0.6414768695831299 0.521880030632019...
13 0.54935222864151 0.6588405072689056 0.5523439645767212 0.686609148979187 0.5536062717437744 0.7021397054195404 0.5507722496986389 0.7048976719379425 0.5507625341415405 0.7086427211761475 0.5514311194419861 0.714877724647522 0.5491073727607727 0.717143714427948 0.5478976964950562 0.7188767790794373 0.548305332660675 ...
14 0.5313548445701599 0.750503420829773 0.5296476483345032 0.749954879283905 0.5257836580276489 0.748713344335556 0.5216497182846069 0.7473850846290588 0.5191332697868347 0.7465765178203583 0.5186328887939453 0.7460673451423645 0.5173474550247192 0.744347482919693 0.5157604813575745 0.7422240972518921 0.514576673507690...
15 0.511537492275238 0.791472390294075 0.5217716097831726 0.7947555780410767 0.5375835299491882 0.7998280674219131 0.5410912036895752 0.8014486581087112 0.5436311960220337 0.8048553019762039 0.5452756285667419 0.8070608079433441 0.5555088520050049 0.8103431761264801 0.5713194608688354 0.8154144734144211 0.5748290419578...
16 0.6727097630500793 0.871819868683815 0.668059766292572 0.8698311448097229 0.6594167351722717 0.86276975274086 0.6482692956924438 0.8560956418514252 0.6242727041244507 0.8467189520597458 0.6169604659080505 0.8395950049161911 0.5790846943855286 0.8269531577825546 0.5646434426307678 0.8180432319641113 0.542766153812408...
17 0.6776787638664246 0.9803337287157774 0.6739026308059692 0.9791278354823589 0.6703395247459412 0.9747967962175608 0.6671603322029114 0.9720479603856802 0.6639297604560852 0.9705040268599987 0.6596173644065857 0.96471793577075 0.648298442363739 0.9611020013689995 0.6438729763031006 0.9565025493502617 0.62440055608749...
18 0.3606736958026886 0.9843928162008524 0.36103877425193787 0.9889697171747684 0.3618197441101074 0.9987596474820748 0.3625430762767792 1.007827339693904 0.3628814220428467 1.0107250194996595 0.3652162551879883 1.0139910420402884 0.36890095472335815 1.0191451124846935 0.371779203414917 1.023171180859208 0.372261077165...
19 0.6838620901107788 0.8325170278549194 0.6839925646781921 0.8335822224617004 0.6842536330223083 0.8357134908437729 0.6844494938850403 0.8373126536607742 0.6840994358062744 0.8378264307975769 0.682701587677002 0.8392567932605743 0.6813029050827026 0.8406879007816315 0.6809523701667786 0.8412023335695267 0.681147754192...
20 0.7324318289756775 0.9978194814175367 0.6945326924324036 0.9857161212712526 0.6909403800964355 0.9895007126033306 0.6825080513954163 0.9868082366883755 0.6644416451454163 1.0058015999384224 0.6650481224060059 1.0109668094664812 0.6614180207252502 1.0147872222587466 0.6620233654975891 1.019965086132288 0.658386290073...
21 0.4487640857696533 0.7239662706851959 0.4395069181919098 0.7199752032756805 0.42788276076316833 0.7125519514083862 0.419077068567276 0.7051542103290558 0.41021284461021423 0.701685220003128 0.39993345737457275 0.6941753029823303 0.3896633982658386 0.686672180891037 0.3766779899597168 0.6818786561489105 0.36645805835...
22 0.6485810279846191 1.0810864642262459 0.6481361389160156 1.0809449553489685 0.6470752358436584 1.0806073397397995 0.6458089351654053 1.080204501748085 0.6447479724884033 1.0798668265342712 0.644303023815155 1.0797252655029297 0.6432886123657227 1.0783471316099167 0.6408705711364746 1.0750621408224106 0.6379864811897...
23 0.38304245471954346 1.0529799312353134 0.38428232073783875 1.0681256130337715 0.3865974247455597 1.096404604613781 0.38785070180892944 1.111713893711567 0.38898223638534546 1.1120725348591805 0.39108365774154663 1.1127386763691902 0.39221516251564026 1.1130973547697067 0.3947087526321411 1.1166048347949982 0.3993438...
24 0.2748337686061859 0.6119195222854614 0.2750059962272644 0.6142981350421906 0.27517834305763245 0.6166782379150391 0.27723827958106995 0.6173412203788757 0.27929800748825073 0.61800417304039 0.2815321087837219 0.621049165725708 0.283767431974411 0.6240959167480469 0.292010098695755 0.6267484426498413 0.3002512753009...
25 0.6526823043823242 0.7381803393363953 0.6528626680374146 0.7396838963031769 0.6532930731773376 0.7432715892791748 0.6538072824478149 0.7475580275058746 0.6542385220527649 0.7511530518531799 0.654419481754303 0.7526615709066391 0.6549056768417358 0.7533015310764313 0.6560652852058411 0.7548279762268066 0.657449722290...
0 0.792009711265564 1.0217725578695536 0.7936449646949768 1.0222947299480438 0.7979124188423157 1.0236573796719313 0.80385422706604 1.0255546104162931 0.8105129599571228 1.027680752798915 0.8169315457344055 1.0297302324324846 0.8221534490585327 1.0313976258039474 0.8252226114273071 1.0323776341974735 0.8257761597633362...
1 0.723814070224762 0.8977898582816124 0.7238232493400574 0.8978624120354652 0.7238495349884033 0.8980701044201851 0.723891019821167 0.898397907614708 0.7239457964897156 0.8988309502601624 0.7240119576454163 0.8993540555238724 0.7240877151489258 0.8999524042010307 0.7241710424423218 0.9006109312176704 0.724260032176971...
2 0.7398257255554199 0.5724636316299438 0.7401332855224609 0.5747578144073486 0.740441083908081 0.5770533680915833 0.7387611269950867 0.5787065625190735 0.7370800971984863 0.5803607404232025 0.7373872399330139 0.5826602280139923 0.7376945614814758 0.5849610269069672 0.7360116243362427 0.5866188406944275 0.7343276143074...
3 0.7852570414543152 0.7947530299425125 0.7854889035224915 0.7964567989110947 0.785984218120575 0.8000970184803009 0.7864423394203186 0.8034638017416 0.7866405844688416 0.804554894566536 0.787811815738678 0.806079164147377 0.7896594405174255 0.8084837794303894 0.7911019921302795 0.8103612512350082 0.7911667227745056 0....
4 1.167439579963684 0.9595569297671318 1.1661689281463623 0.9591486714780331 1.1631386280059814 0.958175141364336 1.1595215797424316 0.9570131674408913 1.1564908027648926 0.9560394696891308 1.1552199125289917 0.9556312002241611 1.1548889875411987 0.9560113847255707 1.154099702835083 0.9569181390106678 1.153157353401184...
5 1.083946943283081 0.8217400461435318 1.0687347650527954 0.8306800127029419 1.0643541812896729 0.8308786600828171 1.062645673751831 0.8287225514650345 1.062444806098938 0.8252303302288055 1.0653125047683716 0.822075217962265 1.0638355016708374 0.8134535998106003 1.0657343864440918 0.8101814985275269 1.0659879446029663...
6 0.9016611576080322 0.9691077414900064 0.9017247557640076 0.96953827701509 0.9018973112106323 0.9707069955766201 0.9021517634391785 0.9724300764501095 0.9024609327316284 0.9745233077555895 0.9027974605560303 0.9768024794757366 0.9031341671943665 0.9790829550474882 0.9034438729286194 0.9811796732246876 0.90369892120361...
7 1.0626249313354492 0.8197412490844727 1.0594282150268555 0.8232920467853546 1.061017394065857 0.8328950554132462 1.0569475889205933 0.8317113965749741 1.0536295175552368 0.8350834250450134 1.0500295162200928 0.8335848450660706 1.0529206991195679 0.8298110514879227 1.0526301860809326 0.8249998539686203 1.0551090240478...
8 1.0416929721832275 0.8084458857774734 1.0385195016860962 0.8119117915630341 1.0392482280731201 0.816536009311676 1.0364024639129639 0.8199242651462555 1.0367342233657837 0.8242687731981277 1.0320954322814941 0.8303476125001907 1.0251855850219727 0.8304949849843979 1.021901249885559 0.8269195705652237 1.02590692043304...
9 0.7463753819465637 0.6499547362327576 0.7497609853744507 0.646571546792984 0.7537712454795837 0.6478675603866577 0.7571496367454529 0.644488126039505 0.7611567974090576 0.6457833051681519 0.7678949236869812 0.6390362977981567 0.775897204875946 0.6416234970092773 0.7792541980743408 0.6382551789283752 0.783252060413360...
10 1.026419758796692 0.7853868454694748 1.0293855667114258 0.8031310886144638 1.0272364616394043 0.8071525543928146 1.0268012285232544 0.8104677349328995 1.0246915817260742 0.8156106024980545 1.017562747001648 0.8238014876842499 1.0183022022247314 0.8282774835824966 1.014561414718628 0.8270723968744278 1.01068091392517...
11 0.9854884147644043 0.7676592916250229 0.987037718296051 0.7772076427936554 0.9918359518051147 0.7832879275083542 0.9949596524238586 0.8024810701608658 0.9917086362838745 0.8059938699007034 0.9924905300140381 0.8108122497797012 0.9892337322235107 0.8143350481987 0.9811534285545349 0.8117315918207169 0.977886676788330...
12 0.8448552489280701 0.7495330572128296 0.8480936884880066 0.7505770921707153 0.8525461554527283 0.7520125657320023 0.8536614179611206 0.7513875067234039 0.8556960821151733 0.7492707669734955 0.8568804264068604 0.7488539218902588 0.8615159392356873 0.7503486275672913 0.8643696308135986 0.7512539774179459 0.86585944890...
13 0.8415020704269409 0.7530143707990646 0.8455381393432617 0.7810358554124832 0.8482384085655212 0.796982005238533 0.8520140647888184 0.8018558472394943 0.8530036211013794 0.8059104532003403 0.8539131879806519 0.8122036308050156 0.8570097088813782 0.816203698515892 0.8587661385536194 0.818884015083313 0.85932546854019...
14 0.8848459124565125 0.8640831857919693 0.8865402936935425 0.8646276742219925 0.8903745412826538 0.8658596128225327 0.8944761157035828 0.8671775013208389 0.8969724774360657 0.8679795861244202 0.8973778486251831 0.867762878537178 0.8983116149902344 0.8667613565921783 0.89946448802948 0.8655249327421188 0.90032440423965...
15 0.9168610572814941 0.921501986682415 0.9067130088806152 0.9182464331388474 0.8910252451896667 0.913213737308979 0.8876731395721436 0.9126318171620369 0.8858288526535034 0.9146225824952126 0.8846347332000732 0.9159114807844162 0.8744731545448303 0.9126520454883575 0.8587645888328552 0.9076135009527206 0.8554059267044...
16 0.764041543006897 0.9010915905237198 0.7685513496398926 0.9020391330122948 0.7760492563247681 0.9001562893390656 0.786353588104248 0.9003630951046944 0.8098263144493103 0.9062075912952423 0.8158570528030396 0.9033715650439262 0.8534119129180908 0.9149181470274925 0.8666457533836365 0.9148962274193764 0.8875644207000...
17 0.7871208786964417 1.0152848362922668 0.7908878326416016 1.0164878461509943 0.7936049699783325 1.0141666950657964 0.7963212132453918 1.013303161598742 0.799408495426178 1.0137779852375388 0.8025528788566589 1.0103804403916001 0.8138346076011658 1.0139845749363303 0.8174096345901489 1.011946776881814 0.83634924888610...
18 1.1285797357559204 1.2287686467170715 1.1293776035308838 1.2334468364715576 1.1310840845108032 1.243453174829483 1.132664680480957 1.252721130847931 1.133055567741394 1.2556126713752747 1.131413221359253 1.2575935125350952 1.1288212537765503 1.2607197761535645 1.1267961263656616 1.263162076473236 1.1265159845352173 ...
19 0.7416572570800781 0.8510667979717255 0.7417954802513123 0.8521338254213333 0.7420721054077148 0.8542687594890594 0.7422796487808228 0.85587078332901 0.7427935600280762 0.8566614240407944 0.7446827292442322 0.8591453582048416 0.7465727925300598 0.8616304397583008 0.7470873594284058 0.8624219596385956 0.7472960352897...

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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) spinal cord 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: